Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: TAXONOMIC MONOGRAPH OF OXYGYNE (THISMIACEAE), RARE ACHLOROPHYLLOUS MYCOHETEROTROPHS WITH STRONGLY DISJUNCT DISTRIBUTION
Review round: 1
Reviewer: 1

Output:
Basic reporting: NB, this reviewer’s comments are numbered consecutively.

1.  This reviewer finds the present ms. to be well within the stated scope of the journal PeerJ.  The ms. is also generally well written and structured in conformance with PeerJ standards (but see added comments below).  The Introduction and Discussion sections are well researched, concise and have a logical ‘flow’, with good contact to relevant literature.

2.  Below is a reference to one recently published article that seems relevant but may not have been seen by the present authors.  They may want to cite it in their revised manuscript:

Sainge MN, Chuyong GB, Peterson, AT. 2017. Endemism and geographic distribution of African Thismiaceae. Plant Ecology and Evolution 150: 304-312. https://doi.org/10.5091/plecevo.2017.1196

3.  On the ‘reviewing PDF’, this reviewer has added comments mainly of an editorial or copy-editing nature.  These annotations should be considered part of this review and are intended to help the authors improve the quality of the final ms. for publication.

4.  This reviewer has also checked the References list and finds an almost perfect, one-to-one correspondence between the entries on that list and the works cited in the main text.  There are just two missing entries, both referring to web sites providing access to on-line databases:

•	IPNI (continuously updated)
•	Thiers et al. (continuously updated)

5.  The ms. describes and names two new species, with methodology in conformance with PeerJ policy and fully meeting the criteria for valid publication in the International Code of Nomenclature for algae, fungi, and plants (McNeill et al., 2012).

6.  This reviewer suggests a slightly different and more descriptive title: "Taxonomic revision of Oxygyne (Thismiaceae), a rare achlorophyllous mycoheterotroph with a remarkably disjunct distribution between tropical Africa and Japan".  The terms ‘systematics’ and ‘taxonomy’ are certainly related, but systematics is broader and nowadays involves examining evidence of evolutionary relationships between organisms/taxa (usually with molecular data).  The authors of the present ms. have reviewed the available literature on the systematics of Thismiaceae and Oxygyne, but they have not presented any new data or analyses along these lines (other than morphological comparisons).  The work is fundamentally a taxonomic revision, and the title should be changed to reflect this.
        According to PeerJ's editorial policy on publishing new species, it is also desirable for the title to mention the new species names (in order to increase visibility & discoverability of this information).  This could be done, e.g., "Taxonomic revision of Oxygyne (Thismiaceae), with descriptions of O. duncanii and O. frankei, two new species from tropical Africa".  The authors should decide if they want to implement this suggestion or stick with a title that emphasises the Africa/Japan disjunction.

7.  Given that the manuscript is fundamentally a formal taxonomic treatment, the structure also needs to be modified somewhat.  In particular, this reviewer recommends that the heading RESULTS should be removed and replaced with the heading TAXONOMIC TREATMENT.  In the present version of the ms. there is no text under this heading, only an abrupt transition to the subheading Key to genera of Thismiaceae.  It is therefore recommended that below the heading TAXONOMIC TREATMENT but before the subheading Key to genera of Thismiaceae, some basic information should be added about the family, similar to the following, with new corresponding entries added to the References list:

Thismiaceae J. Agardh, nom. cons. (Agardh, 1858)
Type genus: Thismia Griff. (Griffith, 1845)
	Achlorophyllous mycoheterotrophs; for complete family description see Stevens (2001 onwards).
	5 genera / approx. 55 species, mostly(?) rare and locally endemic; overall distribution widely scattered mostly in tropical and subtropical forests of South America, Africa and Southeast Asia; in Africa with highest concentration of species in Cameroon (Sainge et al. 2017).

8.  In the RESULTS / TAXONOMIC treatment section, below the key to genera of Thismiaceae but before the beginning of the formal treatment of genus Oxygyne, the present ms. includes 7 short paragraphs of text under the subheading Discovery and extinction.  This text seems out of place or even repetitive with information that is already presented in other parts of the ms., so the recommendation of this reviewer is for the subheading Discovery and extinction to be removed, with the accompanying text also deleted or moved / incorporated elsewhere in the ms.  In the revised version, the start of the formal treatment of Oxygyne would thus immediately follow the key to genera of Thismiaceae.

9.  After the formal treatment of Oxygyne, there are four paragraphs of text under the heading CONCLUSIONS.  This text reads more like a discussion, leading this reviewer to recommend that the heading CONCLUSIONS should be removed and replaced with the heading DISCUSSION.  If the revised ms. is to include a section called CONCLUSIONS then the text under this heading should be no longer than a single paragraph and should appear after the DISCUSSION.  The text of the CONCLUSIONS should be limited to (1) a statement summarizing the paper’s main findings, (2) a more generalised statement about the importance of these findings, (3) perhaps an additional statement about unanswered questions or likely avenues for future work.

10.  The figures in the present ms. are acceptable, but, in both their Abstract and the Introduction, the authors have clearly stated their intention for this work to be monographic.  Given this intended scope, it is a shame there were no photographs or other illustrations provided for three of the six included species, i.e., Oxygyne triandra Schltr., O. shinzatoi (H.Ohashi) Tsukaya and O. hyodoi C. Abe & Akasawa.  This reviewer would like to see photographs or line drawings added in revision so that all of the treated species have at least one illustration.  In the case of O. triandra, the authors have also stated (line 737 of the present ms.) that the illustration in the protologue (Schlechter, 1906) was inaccurate in some respects, making a new illustration highly desirable.  However, there are also some line drawings on the type sheet in B, and if the authors could secure permission to reproduce images of these drawings then these would be acceptable.  Oxygyne shinzatoi and O. hyodoi also have previously published illustrations, and permissions could be sought from the original authors / copyright holders for these illustrations to be reproduced in the present work.  Simply providing references to previously published illustrations is unacceptable for a work purportedly of monographic scope.
Experimental design: 11.  Materials and methods are perfectly fine for a work of this nature.  The permits obtained by the first author to conduct field-work in Cameroon appear to be in good order.
Validity of the findings: 12.  This reviewer certainly agrees with the authors’ findings concerning the two new species described in the present work.  The larger scope of the work (comprehensive revision of the entire genus) greatly enhances the value of these descriptions.

13.  The most intriguing finding in the present work is that the newly described Cameroonian species Oxygyne duncanii appears closer morphologically to the three Japanese species than it does to O. triandra (of which the only known locality is about 12 km away from the type locality of O. duncanii).  The authors have further noted (on lines 822824 of the present ms.) that if future molecular data support the distinction of Oxygyne and Saionia Hatus. as separate genera, then morphological comparisons indicate that O. triandra and Central African O. frankei would be placed together in Oxygyne, whilst O. duncanii and the three Japanese species would be placed together in Saionia.  On lines 817821 they list four characters uniquely shared by O. triandra and O. frankei and seem to be of taxonomic importance: (1) erect very narrowly triangular to caudate perianth lobes; (2) dark brown lines (corresponding with the vascular supply) extending from the base of the perianth tube to the base of each perianth lobe; (3) reduced lamellae which are too small to occlude the perianth tube mouth; (4) a stigma with three subulate curved-erect lobes only, lacking lateral lobes.  On the other hand, in their key to species of Oxygyne (starting on line 322), the leads of the first couplet have to do with geography and the colour of the flowers.  While it may be true that the key should be viewed as nothing more than an aid to species identification, the fact remains there is a fundamental mismatch between the characters mentioned in the first couplet of the key on the one hand, and in the authors’ later discussion about characters of subgeneric or possibly generic importance.  The authors need to address this mismatch somehow, either by fundamentally revising the key to Oxygyne species or by adding to the later discussion about subgeneric/generic characters a further note about the unnaturalness (artificiality) of the characters used in the key
Additional comments: No additional comments.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: TAXONOMIC MONOGRAPH OF OXYGYNE (THISMIACEAE), RARE ACHLOROPHYLLOUS MYCOHETEROTROPHS WITH STRONGLY DISJUNCT DISTRIBUTION
Review round: 1
Reviewer: 2

Output:
Basic reporting: I consider that the manuscript meets all Peerj standards. The presentation of text is professional and authorative but at the same time very readable. It is very comprehensively referenced. Many primary references are obscure and might prove difficult to access, but this is inevitable when dealing with little-known taxa in remote localities
Experimental design: It is perfectly clear what the authors are aiming to achieve. For the sake of providing a detailed overview of all the species that the authors now consider to belong to Oxygyne, they have had to lean heavily on historical accounts as they had no first-hand access to living or pressed material of some taxa. This isn't ideal but I sense they have been as meticulous and objective as possible in drawing conclusions regarding taxa they have no experience of.
Validity of the findings: The conclusions are well stated and represent an important contribution to the taxonomy of a complicated and controversial group of heteromycotrophs. The authors concede that further generic ressignments are possible following molecular analyses, but given that at least two of the six taxa are extinct and others are proving so hard to locate, I can't see the molecular work being done anytine soon.
Additional comments: Despite this monograph dealing with a group of plants that are so little known and elusive that the vast majority of botanists are ever likely to encounter them, this monograph is very readable. It is interesting from a taxonomic perspective, intruiging from a phytogeographical perspective, and deeply depressing from a conservation perspective!

There is little to criticise. For the sake of completion, taxonomic decriptions of two of the Japanese species are reproduced verbatim from the monograph of Dr Tsukaya. They are substantial slabs of text, so I assume permission to do this was sought and obtained (if Dr Tsukaya is still alive, which I hope he is). I was surprised not to see him included in the acknowledgements. On a related note, the description of hyodoi is stated to be modified from Tsukaya, but I don't how this is possible given that none of the authors have seen the plant, alive or dead.

Given that the photos of duncani (Fig 4) were taken by the first author, there is scope to improve some of them. The two photos on the left of the plate can be closer views, because what is surrounding the plants is of no biological interest. Top right is basically a photograph of a penknife. I did eventually locate the in situ plant that is being referred to but if this image is to be retained at the same scale there need to be an arrow showing where it is. Bottom right is spoilt by sloppily allowing a hand lens to obscure most of the ruler included for scale.

The photos of root structure are fantastic but are they providing info on generic or sub-generic affiliations that wasn't present before?.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EFFECTS OF PRESERVATION METHOD ON CANINE (CANIS LUPUS FAMILIARIS) FECAL MICROBIOTA
Review round: 1
Reviewer: 1

Output:
Basic reporting: Areas for improvement
•	Are the raw sequencing data files uploaded to a publicly available database? I did not see this noted in the methods.
•	Fig. 3 – need buffer symbols in the weighted diagrams.
•	96 samples were prepped, but the PCoAs only show ~34 samples  - what happened to the other samples?

Minor concerns
•	Methods: Did the donor have any recent antibiotic exposure? (This information isn’t critical to you study, but it would be worth mentioning this history in the methods.)
•	Need a period after the reference in line 120, 293, 297 and line 368 and 377 – did you intend to have a line break here? (Please check carefully throughout the paper to ensure appropriate punctuation.)
•	Fig. 2, S1, 5A,B – mention if the error bars SD or SE in the legend.
•	Fig. 2 and 5 are a little challenging to read because the location of the error bars distort the shapes, so it becomes difficult to tell the circles / triangles / squares apart. If you are considering publishing in color, the use of color in these graphs may be helpful.  Otherwise, you could also consider adding varying dashed lines between points to make it easier to tell each method apart.
•	Line 289 – “Assessing changes in preserved fecal microbiota over time provides insight on…” – suggest adding the word “preserved” to this sentence to clarify.  Can also remove the word “would” and use “provides” instead of “provide”
Experimental design: Currently the authors provide statistical results for DNA concentration and purity, alpha diversity, and PERMANOVA results indicating that there are “effects on bacterial community of storage buffer, temperature, and duration”; however, these effects are never explored statistically. Instead, the authors focus on high level (phyla/class) taxonomy summaries and PCoA visualizations.  This study would be greatly improved by further statistical analysis at the genus / OTU level to answer questions like – are there any microbes/OTUs that differ significantly between preservation treatments? Do any of the methods  bias / enrich the preservation of particular microbes / OTUs? (This can be accomplished in QIIME: group_significance.py and supervised_learning.py.)

Critical areas for improvement:
•	Lines 206-218: There are no figures or detailed results provided for the alpha diversity results. The results state that buffer, storage duration, and temperature had statistically significant effects on the various alpha diversity metrics (Shannon, observed species richness, evenness) - but do not indicate which buffer / duration / temperature had higher/lower diversity metrics.  This is important information to share either in figures or words so that readers will be aware of how microbial diversity can be affected by storage method.
•	My interpretation of Fig 4A,B are that NOT all day 0 samples look the same.  Samples preserved in ethanol or RNAlater – even for just 1 hour prior to extraction at Day 0, look different than samples without a buffer or with glycerol:PBS.  This is detectable at a phylum level, which means there is a very strong and rapid bias introduced by these preservation methods. In order to understand this better, analysis at the OTU level is required followed by interpretation of these results.
•	Fig. 5C reports mean fold change of frozen samples compared to “fresh samples.”  Were all Day 0 (“fresh”) samples combined for this analysis?  As suggested above, I do not believe that all Day 0 samples are comparable / similar and that RNAlater and Ethanol may have introduced some taxonomic biases into preservation even at Day 0.  I suggest removing this analysis. Deeper OTU level analysis will provide more thorough statistical results to explore for changes over time introduced based on buffer.

Minor concerns
•	Fig. 6 is not a particularly valuable analysis and can be removed from the paper. The microbial community actually show this same result in much more detail (see Fig 4A), and through taxonomic analysis (at higher taxonomic levels and the OTU level) you can provide a deeper interpretation of these results rather than a correlation. (For example, after appropriate analyses, you may be able to say something like: Day 0 microbial communities all contained Fuso / Proteo but these microbes appeared to degrade in the glycerol / no buffer methods over time (except at -80C) as they were no longer identifiable / significantly decreased from Day 7 – Day 56 at 25C and 4C.) OTU level analyses may identify several other biases in the data by storage method that will be valuable to report.
Validity of the findings: •	Line 326-327 – this study in this reference was only done for 72 hours, so it is misleading to suggest (based on this reference) that refrigeration would be adequate storage when your study was for much longer - 56 days. Additionally, in your study, microbial communities were examined at the level of phyla and class – which are very high taxonomic levels. Genus and species differences are potentially much greater over time and by buffer, and these types of changes are likely more important and relevant to any type of health or research study. No data / results are provided at the genus/species taxonomic levels, so again, suggesting that refrigeration is adequate is not appropriate here.  (However, if you do perform analyses at the genus or “OTU” level and find no significant differences between time/buffer for refrigeration, then you can certainly make the conclusion that refrigeration of fecal samples over 56 days is reasonable. I suspect this will not be the case.)
•	Lines 175-177 – Interesting that DNA quality declined across all preservations methods but only at Day 14 (but not day 56). Potentially suggests an external factor – new/different person did the extraction that day? New/different reagents? Accidental minor modification to extraction protocol?
•	Line 292 – “This approach”  - what approach? – are you referring to preservation of microbiota? This seems unrelated to the reference in this sentence which is about how microbial gene expression can be used to predict the cellular and environmental states from which a microbe was derived.
•	Line 292-300 – It is true that microbial forensics is a growing field both to understand microbial environmental exposures based on gene expression as well as to understand processes like decomposition and historic pandemics; however, why spend a full paragraph on microbial forensics?  It is my understanding based on the 3 references included in this paragraph that these techniques focus on examining present microbes in order to interpret past events rather than “preserving” DNA to examine in the future. Either add a clearer explanation of the value of DNA preservation within this forensic context or perhaps choose to highlight other areas in which DNA preservation is critical (e.g. field studies that don’t have immediate access to labs, research/clinical studies in which DNA must be preserved for future sequencing)
•	Lines 374-377, providing clinical relevance of Coriobacteriia is not especially helpful when presented in this way.  You could link it to your preservation study (e.g. There was a bias toward preserving (or promoting the growth of?) Coriobacteriia in glycerol preservation. This bias is important to know because Corobacteriia has clinical relevance and could falsely be identified as increased if an individual used this preservation method.)
•	Lines 378-379 – remove, this seems like a random statement / reference here. (1. Your study focuses on “unbiased” microbial community preservation not selective bacterial enrichment. 2. Your results and conclusions highlight that freezing is more effective than room temp preservation.)
•	Lines 388-391 – These 2 sentences seem to contradict each other.  The first sentence says there’s not much difference between samples stored at 4 and -80; the second sentences days temperature is important because it has an additive effect combined with buffer. Within that same sentence it is also stated that preservation is really driven by buffer.  Suggest rewording for clarity.
•	Depending on the OTU-level analysis, it may be important to discuss the possibility that some microbes were enriched at room temperature or 4C.  (For example, while your DNA concentration results indicate relative stable DNA concentrations from day 7-56 at the lower temperatures, this may be because some microbes bloomed while others died / DNA degraded. Concentration results should be evaluated within the context of OTU analysis.  As a researcher, I don’t just want high DNA concentrations, I want to know that I am accurately preserving a microbial community, so if I get high DNA concentrations but they are concentrations of microbes that bloomed while in the refrigerator – this is not a useful preservation method.
Additional comments: This manuscript describes an important and technically sound study examining various preservation methods (25C, 4C, -80C, RNA later, 70% ethanol, 50:50 glycerol:PBS) for canine stool. As investigations of the microbiome continue to grow in number and value, it will be critical for clinicians and researchers alike to understand how various preservation methods affect their samples and what the best options are for preservation. Additionally, this study introduces the value of combining preservation methods (both temperature and buffers) in order to achieve optimal results. That said, one of the important areas for improvement is a deeper analysis of the microbial community data. The importance of DNA preservation lies in the ability to maintain microbial communities over time that accurately represent the microbial communities present in the non-preserved, immediately extracted sample. If samples are only analyzed at the phylum (or class) level, then there is no way of knowing if specific OTUs were maintained over time or by each buffer – which undermines the value and power of this experimental design.

Thank you for allowing me to review this well-designed study and all the best!


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EFFECTS OF PRESERVATION METHOD ON CANINE (CANIS LUPUS FAMILIARIS) FECAL MICROBIOTA
Review round: 1
Reviewer: 2

Output:
Basic reporting: No comment
Experimental design: Fatal flaw: n=1
Validity of the findings: no comment
Additional comments: The authors have described a study evaluating the effects of storage temperature and preservation buffers on fecal microbiota of dogs.  This study may have been of interest if done properly. Unfortunately, only 1 animal was sampled so it is unlikely that the results can be applied to any population. An n=1 is not useful. Disease, drugs, diet, etc. can all drastically affect gastrointestinal microbiota populations that will differ greatly in their resistance to temperature, oxygen exposure, freeze-thaw cycles, preservation buffers, etc.  Therefore, I find that this is a fatal flaw and not worth reviewing the paper. Other papers with the same goals have sampled multiple humans or animals and I feel the same must be done here to be valuable.

Here are just a couple examples in recent years:
-Gorzelak et al., 2015, PLoS ONE 10:e0134802 (4 people)
-Anderson et al., 2016, Sci. Rep. 6:31731 (16 people)
-Blekhman et al., 2016, Sci. Rep. 6:31519 (13 rhesus macaques)


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EFFECTS OF PRESERVATION METHOD ON CANINE (CANIS LUPUS FAMILIARIS) FECAL MICROBIOTA
Review round: 2
Reviewer: 1

Output:
Basic reporting: NA
Experimental design: NA
Validity of the findings: NA
Additional comments: The authors have thoroughly responded to reviewer comments and added several helpful analyses, interpretations, and clarifications to their manuscript. I suggest only the minor revisions listed below.

Line 219: "the interaction between storage buffer and temperature (F-value=3.443, DF=3, P=0.22) […] significantly affected observed species richness levels (Fig. S3)."  - The way this sentence is written looks like the buffer/temperature interaction "significantly affected" - but the p value (0.22) is not significant? (Fig S3 indicates this interaction should be p = 0.022)

Line 214-215: "Storage buffer had a statistically significant effect on Shannon Diversity Index values (F-value=3.07, DF=3, P=0.03)." - Results should include post-hoc tests to determine what/which buffers have significantly different Shannon diversity values. (Your readers will be especially interested to know which buffers are most effective at preserving / maintaining a combination of richness/evenness (Shannon).)

Lines 217-221: "the interaction between storage buffer and temperature (F-value=3.443, DF=3, P=0.22), and the interaction between storage buffer and duration of sample storage (F-value=9.67, DF=3, P<0.00001) significantly affected observed species richness levels (Fig. S3)." - Results should ideally include post-hoc tests to determine what combinations within the interactions have significantly different observed species richness levels. This could be in a supplemental table.

Line 221-225: "In addition, for species evenness, we found that there were significant effects associated with interactions between storage buffer and storage temperature (F-value=3.98, DF=3, P=0.01), storage buffer and duration of sample storage (F-value=4.9, DF=3, P=0.004), and buffer, storage temperature, and duration of sample storage (F-value=3.1, DF=3, P=0.03) (Fig. S4)." - Results should ideally include post-hoc tests to determine what combinations within the 3-way interaction have significantly different observed species evenness. This could be in a supplemental table.

Line 241-245: Need to italicize microbial genera. (Also in legend of Fig. 4) - check throughout the rest of the document for this (i.e. line 263, 271-273, 280)

Line 262: Replace "phyla" with "taxa"

Line 270: Fig. 5C is listed in the manuscript but I only see 5A and 5B in the figures.

Line 276: PCoA's are just a visualization (not an "analysis") - unless you ran a statistical analysis (i.e. PERMANOVA) and can list the results? Lines 276-278 state that Weighted PCoA  demonstrates that "RNA clustered very closely with those in fresh control samples." When I look at Fig. 3 It looks like RNA samples cluster somewhat separately (on their own) from fresh control samples. (Do you have a statistical analysis based on the distance matrices that indicates that RNA samples are not statistically distinct from fresh control samples?)

Line 234-237 states: "Analysis of weighted and unweighted PCoA plots show that most Day 0 samples (in red) clustered together, indicating a high degree of similarity among samples extracted regardless of buffer preservation at the starting time point." However, line 288-290 states, "Storage with both RNAlater and 70% ethanol rapidly introduced permanent changes in microbial composition after a 2-hour incubation period on Day 0." Consider rewording lines 234-237 for consistency.

Line 440: remove "both" (or move "both" before "effective")

Line 475: Suggest rewording to "creating a preservation bias that could be falsely interpreted as a clinical concern"

Line 547: Suggest removing "comprised of genera Streptococcus, Prevotella, Collinsella, and Megamonas."


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EVIDENCE-BASED ECONOMIC ANALYSIS DEMONSTRATES THAT ECOSYSTEM SERVICE BENEFITS OF WATER HYACINTH MANAGEMENT GREATLY EXCEED RESEARCH AND CONTROL COSTS
Review round: 1
Reviewer: 1

Output:
Basic reporting: I found this manuscript easy to read and comprehend.  The grammar and sentence structure is well-conceived and presented.  Overall and excellent manuscript one that is worthy of publication.  The literature review was very good and many of the more important articles were referenced.  I did find several cases where materials and methods were repeated in the results section and these need to be located and removed.  I do understand that a large part of this manuscript type requires a detailed explanation on logic and processes involved in formulating the approach – maybe it would be prudent to simplify the materials and methods section and include portions in the actual results to help the reader understand the reasoning better.  The figures were adequate.
Experimental design: The experimental design was conceived and executed with no real issues.  I thought the explanations were very clearly given which allowed me to easily understand the scope and breadth of the research.  The authors clearly presented the pros and cons of their approach and adequately justified omissions when needed.  While other manuscripts have addressed the issue of the effectiveness of the water hyacinth biocontrol agents the combination of various models adds credence to the generally accepted notion of the agent’s impact.
Validity of the findings: In general I have no real issues with the findings.  As stated earlier the authors adequately address strengths and weaknesses of their methods and how they relate to their conclusions.  While the impact of the water hyacinth agents have been shown to be effective in previous publications the additional depth the authors went through just adds credence to this accepted idea.
However, to many people the agents are not thought to be effective although numerous manuscripts and popular articles have attempted to validate such.  Reasons for this are many but the main one is water hyacinth still exists and in many areas it is still a massive problem.  Control methods continue, people still have difficulties navigating through such areas, and there are no real signs that are easily observable to make these people believe the problem is getting better.  I had hoped that the authors would address such concerns and attempt to alleviate such issues but I see no evidence of that.  Another issue that is not addressed is why these perceptions of less than satisfactory agent’s impact occur.  One was addressed above but another is the highly successful use of alligatorweed biocontrol agents – the first target addressed in the aquatic plant world.  That program was so inordinately successful that it is recognized as a prime example of weed biocontrol.  With the release of the agents on alligatorweed control was achieved in months and not years as is the case for water hyacinth and gave people the false expectation that such amazing control is the norm and not the exception.  Perhaps this is outside the realm of this manuscript but might help address some of the perceptions people have as to the non-effectiveness of water hyacinth agents.
Additional comments: I believe I addressed general comments previously.  Have the authors re-check citations I did find a few missing though I did not go over the list in detail.  Also, a minimal number of more specific comments have been placed in the manuscript itself.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EVIDENCE-BASED ECONOMIC ANALYSIS DEMONSTRATES THAT ECOSYSTEM SERVICE BENEFITS OF WATER HYACINTH MANAGEMENT GREATLY EXCEED RESEARCH AND CONTROL COSTS
Review round: 1
Reviewer: 2

Output:
Basic reporting: The article is generally well written, and sufficiently under-built with literature references. I have the following suggestions for improvements:
1. The Introduction section is quite lengthy, and does not read well. I would suggest the authors condense this section by 20-30%, and steer clear of overly-long phrases and rather colloquial language.
2. The Introduction section may benefit from a short additional paragraph in which the (exceptionally-high) benefit:cost ratios of biological control are already illuminated (Greathead & Greathead; Cock et al.), and in which the dearth of ex-post economic studies of this practice is mentioned (evt. citing Naranjo et al., and others).
3. The authors could consider adding in more concrete data in the Abstract - e.g., highlighting the 84% decline in growth rate, $4.45 billion in ecosystem service benefits.
4. The Methods section can be further streamlined. Also, certain parts of the Methods (e.g., line 203-207) may fit better in the Results section.
5. Some reference appear to be missing in the Reference section.
6. There are occasional typos in the text (e.g., line 172, line 481).
Experimental design: Overall, the research questions are properly defined & the methods appear to be sound. I would like to see a greater effort to dis-aggregate control effects due to biological control versus those of 'integrated control' (i.e., combination of  mechanical, herbicidal and biological control).
With the wealth of data that the authors have at their disposal, I believe it should be possible to generate spatially-explicit information on amount/coverage of herbicide sprays and mechanical harvesting for a particular year (or multi-year time period). Next, contrasting waterhyacinth cover declines in areas with varying intensity of different control tactics can provide a ways of assessing the level of weed suppression through biological control (as compared to 'integrated control'). These data possibly can also be shown in a graph, or map. Another way of quantifying the relative contribution of biological control is by mapping Neochetina distribution/abundance, and contrasting shifts in usage of alternative measures (mechanical/herbicidal) following the local establishment/impact of a given agent. A third way of contrasting the added benefits of biological control is by contrasting inter- and intra-annual level of cover reduction of waterhyacinth due to mechanical/herbicidal interventions, before/after local establishment of a given agent.
Validity of the findings: The findings are exciting and important, and illuminate the impressive (economic / environmental/ societal) benefits of Eichhornia biological control. Yet, these findings are not emphasized sufficiently in the Discussion and Conclusion sections. I would suggest the following steps to remediate this:
1. Instead of starting off with a listing of key weakness of the study, I'd rather initiate the Discussion section with a brief overview of the main findings, to then go more in depth into each of these in the consecutive paragraphs.
2. The current benefit:cost ratio is high, but does indeed cover 'integrated control'. As also indicated above, I'd appreciate if the authors can make further efforts to split out costs/benefits of biological control versus 'integrated control'. It is possible that the benefit:cost ratio for solely biological control is far higher than for integrated measures (possibly nearing some of the figures as attained in Africa).
3. Though the study centers on Louisiana, it is important to emphasize that the investment in biological control research benefited areas far beyond the state's border (as mentioned briefly in line 347). Hence, spatial coverage of the BC endeavor far surpasses this of a single herbicide spray or mechanical removal of waterhyacinth mats. This should be duly emphasized when discussing benefit:cost results and broader impacts of the biological control campaign.
4. Control costs in Table 3 are eye-opening & clearly show the comparatively low cost of biological control both in terms of research and deployment/application. These kinds of results should receive proper coverage in the Discussion section - and a greater effort could be made to underline the self-propagating nature of biological control, and the sustained accumulation of ES benefits over time (as compared to herbicidal control, which comes with yearly repeating cost) - even while BC releases stopped in the 1980s (line 167).
5. End your Conclusions section with an over-arching statement that -aside from stressing the value of generalizable models- duly illuminates the socio-economic importance of biological control.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: EVIDENCE-BASED ECONOMIC ANALYSIS DEMONSTRATES THAT ECOSYSTEM SERVICE BENEFITS OF WATER HYACINTH MANAGEMENT GREATLY EXCEED RESEARCH AND CONTROL COSTS
Review round: 1
Reviewer: 3

Output:
Basic reporting: This is a very well written manuscriupt that flows logically, with sufficient background to place the study into an ecologically and economically relevant context.
Experimental design: While I am not an economist, the methods were written in such a manner that I understood exactly what the paper set out to do, without having to read up on economic modelling or cost-benefit analyses.
The research highlighted an incredibly important issue: how easy it is to forget how bad a situation used to be, and not value the economic and ecological benefits accrued over a significant period of time. The authors are to be commended on selecting a very pertinent topic to aquatic weed conntrol, with international relevance.
Validity of the findings: The findings of the study highlight the benefit of controlling the world's worst aquatic weed, using an economic cost-benefit analysis. Four benefits were assessed, and used to derive the C:B ratio. The authors then discuss how the value may be underestimated, because other benefits could not be included in the study due to incomplete data, thereby evaluating the relevance of their results.
The C:B ratio derived from this study is sure to be very well cited in the future, in other studies justifying the need for biological control of aquatuic weeds, in general.
Additional comments: I really enjoyed reading this paper, and could find no fault or manner to improve it.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: IMMUNOGENICITY EVALUATION OF MS2 PHAGE-MEDIATED CHIMERIC NANOPARTICLE DISPLAYING AN IMMUNODOMINANT B CELL EPITOPE OF FOOT-AND-MOUTH DISEASE VIRUS
Review round: 1
Reviewer: 1

Output:
Basic reporting: Although generally adequate the quality of the English could benefit from help from a native English speaker.
Terminology could be improved. For example the full details of the FMDV used should be given and the sequence that was used should be referred to as the "FMDV VP1 G-H loop" and this used throughout.
What is PepVac? I could find no information on this. The authors imply that it is a vaccine that is in commercial use - is this the case or is it a synthetic peptide that was made under contract?
What was the template used for amplification of the VP1 G-H loop sequence? Presumably FMDV. If so, what serotype and what was the sequence?
Line 85 - how many repeats were linked?
Line 96 - how much 1M NaCl was used?
Line 117 - what about PepVac?
Line 127 - How much antigen does 100ul of PepVac contain and what is the antigen?
Line 148 - what is WST-8? Define.
Line 167 - Which restriction enzymes were used and where did they cut?
Fig 1 legend - What are upstream and downstream fragments and where is whole fragment? What is SOE-PCR product? What is Fig 1B? What was used for digestion?
I found the figure legends generally unsatisfactory.
There should be a diagram of the cloning strategy.
Fig 2 legend - what is meant exactly by lysate supernatant and lysate precipitate?
Fig 3 - there are no controls. Unmodified MS2 particles and an irrelevant peptide for example.
Fig 4 - the particles should be shown at a higher magnification.
Fig 5 - the responses look quite similar at 1/20. Were dilution series tested to get a better idea of the relative responses? Did the boost do anything? - what happens is they are not boosted? Do the titres still rise?
Experimental design: The experimental designs are appropriate for the aims of the study but much clearer and more detailed descriptions should be given (see 'basic reporting' section).
However, it has been known for decades that immune responses to peptides can be improved by linking sequences designed to provide T cell help. Why was this not done with the tandem repeat construct?
It has also been known for many years that the ability of peptide vaccines to induce protective responses is species specific and small laboratory animals are far easier to protect than commercial target species. No attempt was made to test or address this problem.
Validity of the findings: This study differs little from the observations publish by Dong et al (as referenced) who also made chimeric MS2 VLPs incorporating sequence of the FMDV VP1 G-H loop. The authors should describe how their study adds to the already published literature.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: IMMUNOGENICITY EVALUATION OF MS2 PHAGE-MEDIATED CHIMERIC NANOPARTICLE DISPLAYING AN IMMUNODOMINANT B CELL EPITOPE OF FOOT-AND-MOUTH DISEASE VIRUS
Review round: 1
Reviewer: 2

Output:
Basic reporting: -
Experimental design: -
Validity of the findings: -
Additional comments: Wang et al. report a potential chimeric nanoparticle-based vaccine (CNP) against the Foot-and-Mouth disease, which is a viral infectious disease of cloven-hoofed animals. They generated the CNP vaccine, and analyzed its immunological responses in mice, in comparison with other type of vaccines, such as, a commercialized vaccine PepVac. I have come comments, below:

1. In general, an abbreviation should be used after its full name/word has been mentioned. For example, in the abstract, should FMDV stand for the Foot-and-Mouth virus? Although, a full name/word and its corresponding abbreviation have already been mentioned in the abstract, when they come into the text (i.e., in the introduction part), should they be mentioned again in full name/word before its abbreviation could be used? Please check the use of abbreviations throughout the manuscript. For example, Line 55, what does 'AP' stand for? Line 62-64, CNPs, TRE, and PepVac stand for? Line 122, AEC?

2. The first sentence of each paragraph should be indented.

3. Please have a native English speaker proofread the manuscript to ensure clarification and grammar of the text.

4. Line 69, should the total number of mice be mentioned here?

5. Line 74, for those who may not be familiar with this type of vaccine, what is the meaning of 'peptide 2600+2700+2800'?

6. Line 75, the authors should give brief detail on how to produce the anti-polypeptide (140-160 of VP1) monoclonal antibody or provide the references.

7. Line 77, recombinant protein(s) and plasmid DNA map(s) (with a label of each constructs) should be provided as a figure in the manuscript or the supplementary data.

8. Line 80, what is the PCR template used to amplify the G-H loop?

9. Line 81, is it OE-PCR or SOE-PCR? Please provide a reference.

10. Line 89, E. coil should be spelled out in full, when first mentioned.

11. Line 97 and 101, 'rpm' stands for 'round per minute' already. No need for '/min'. Actually, if the authors could provide a centrifugation rate in term of 'x g', it will be more useful for reproducing the experiments.

12. Line 118, please provide additional information on how to maintain and inactivate FMDV, or at least provide a reference.

13. Line 120 and 132, where the pig anti-FMDV/O hyper immune serum and the rabbit anti-FMDV serum came from? (commercialized source? reference?)

14. Line 130, did pre-immune serum samples from mice were included in the experiments?

15. Line 135, why did not coat the inactivated virus directly onto the 96-well plate?

16. In the Methods section, please provide a source of each commercial product, such as, Line 137, goat anti-mouse IgG-HRP.

17. Line 163, 's,' ?

18. Line 166, what bands are expected for the RFLP?

19. In general, Figure legend should include adequate information for its described figure, without going back to the text. Markers should be used to indicate the bands in the gel. For example, in Figure 1, the authors should indicate the size of each band. In the legend for Figure 1B, what restriction enzymes were used? In Fig 1A, cannot see the expected band in Lane 3.

20. Figure 5-7, the use of asterisks (*, **, ****) are very confusing, please revise accordingly. In the Figure legend and table description, if possible, use of abbreviations should be avoid, for example, in Figure 6, CoA, dpv, and FMDV.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: IMMUNOGENICITY EVALUATION OF MS2 PHAGE-MEDIATED CHIMERIC NANOPARTICLE DISPLAYING AN IMMUNODOMINANT B CELL EPITOPE OF FOOT-AND-MOUTH DISEASE VIRUS
Review round: 2
Reviewer: 1

Output:
Basic reporting: -
Experimental design: -
Validity of the findings: -
Additional comments: A minor correction: Escherichia coli, not Escherichia Coli


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: SAMPLE ENTROPY ANALYSIS FOR THE ESTIMATING DEPTH OF ANAESTHESIA THROUGH HUMAN EEG SIGNAL AT DIFFERENT LEVELS OF UNCONSCIOUSNESS DURING SURGERIES
Review round: 1
Reviewer: 1

Output:
Basic reporting: This study is to address a novel method of EEG singals for monitoring the depth of anesthesia. The manuscript is well rewriten, and stucture of this manuscript is good.
Experimental design: Data and analysis is OK, the research issue is definition.
Validity of the findings: The findings of this study are OK.
Additional comments: I have carefully read this manscript. Authors used some existing method to analyze the EEG, including EMD and sample entropy, then used a ANN to model the sample entropy with BIS. I did not find any novel idea and method in this MS, and the sample size is small, too.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: SAMPLE ENTROPY ANALYSIS FOR THE ESTIMATING DEPTH OF ANAESTHESIA THROUGH HUMAN EEG SIGNAL AT DIFFERENT LEVELS OF UNCONSCIOUSNESS DURING SURGERIES
Review round: 1
Reviewer: 2

Output:
Basic reporting: This paper studied a new method to assess the depth of anesthesia (DoA). Authors claimed that the SampEn feature derived from EEG is proved to be able to distinguish the selective traditional 3 stages of anesthesia.
 The reviewer thought the development of methods/algorithms for automatic classification of EEG is very important because of the large variability of the responses of patients to drugs and noxious stimuli during a surgery. Totally, the abstract is concise and clear for introducing the body of paper, the results sound interesting and conclusion was convincing. The manuscript is well organized and the logic is clear. I only have a couple of concerns I would like the authors to address before publication:
Experimental design: 1-	The data is not relatively comprehensive. The database should be described in more detail. Please mention type of drugs used during different stage of anesthesia.
2-	Introduction should provide more information regarding advantages and disadvantages of proposed method in comparison with the nonlinear measure with an application of depth of anesthesia. Actually, the introduction should provides sufficient research background about current studies of DoA system.
3-	Additional information should be provided about the rationality that supports the selection signal processing techniques. What kind of properties can be evaluated by applying them? What is the justification to select the SampEn instead of the frequency-based band or other non-linear features?
Describing the properties of the algorithms will help to understand the properties that must be present in the EEG signal that are related (correlation) to level of consciousness. A better approach is to describe the behavior of the EEG as a function of the depth of consciousness and apply the signal processing algorithms that are suitable to extract the features or the feature values.
4-	Is there any preprocessing for EEG signal? It seem that there are many noise embedded in EEG signal.
Validity of the findings: 5-	The validation of the proposed method presented in the manuscript is quite limited. Please compare your result with permutation entropy methods or recurrence analysis which have used by many authors in recent years.
6-	In this paper, the authors have used ANN classifier. The comparison with existing classification methods, such as SVM and Random Forest, should be considered.
7-	Discussion section should provide more information regarding advantages and disadvantages of proposed method in theory in comparison with the linear and other non-linear approach such as Permutation Entropy, Fractal measures and recurrence quantification analysis.
8-	Statistical analysis is week and I recommend go through more.
Additional comments: 9-	A brief summary of the significance of each figure and table in its heading would help readers to understand the figure and tables quickly without having go to the very details.
10-	The manuscript has to go also through careful proof-reading as some of the text is hard to understand because of the grammatical problems.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: AN IMPROVED PRIMER SET AND AMPLIFICATION PROTOCOL WITH INCREASED SPECIFICITY AND SENSITIVITY TARGETING THE SYMBIODINIUM ITS2 REGION
Review round: 1
Reviewer: 1

Output:
Basic reporting: The manuscript is well written and follows a construction that adheres to the typical formatting guidelines required of original research. The authors provide a fair representation of the state of the field, however, some important references are missing in support of statements, and these are detailed in the relevant sections below. The samples analysed in this study are part of a larger set of samples collected in the TARA Oceans/Pacific voyages, which have committed to providing the RAW sequenced data. This is detailed in the manuscript. While it is clear that this manuscript is a precursor to forthcoming analyses of much-larger datasets, the relatively simple set of experiments represent a stand-alone manuscript and not the inappropriate subdividing of data.
Experimental design: The aims and objectives are clearly stated and the study addresses a knowledge gap that will be of interest to many coral/Symbiodinium biologists. The methods are generally well-described with sufficient detail if to be repeated. However, there are some concerns as to the factorial design regarding the optimisation of the SYM_VAR primer set and that what was carried out does not match the stated objectives. One of the objectives was to test the number of cycles on the detection of Symbiodinium in samples where cells may be naturally low in abundance (e.g. environmental samples such as open ocean water). Line 255 – “…and whether an increase in the number of PCR cycles actually aids in the amplification of Symbiodinium from samples representing Symbiodinium-rare environments”. However, the opposite was performed during optimisation. Cycle number was actually decreased from 35 cycles, which is the standard protocol for all primer pairs outlined in table 1, to 30 or 25 cycles depending on the treatment. This does not accomplish the objective as directly stated above and is somewhat perplexing. If you have a more specific primer set, why wouldnt you take your cycle number from 35 to 40, or higher, to better detect rare sequences? This objective needs to be either reworded or removed and the results/discussion altered accordingly. Further complications include a optimisation design that is not fully factorial. For example, you find minor differences in the chimeric reads across the two cycle-number treatments, but could this difference be due to the change in annealing temp to 59 C?  Why was a 59 C treatment with 35 cycles not conducted? Again, the objective likely needs to be reworded to reflect what was actually conducted. I suspect this lack of a fully-factorial design is also what precluded the use of simple, but informative, statistics that validate the differences seen across the different optimising treatments. While these are relatively straightforward optimisation steps that other researchers could also conduct, one expected outcome of this manuscript is for labs/groups to decide whether or not to adopt this as their new standard protocol, and this ambiguity makes the choice substantially more difficult.
Validity of the findings: The finding that the SYM_VAR primer set is significantly more specific for Symbiodinium is quite remarkable and is the main finding of the manuscript. An extra 20 to 30% of the sequences being assigned to your target organism is a non-trivial improvement that will appeal to many people in this field, especially as the costs associated to NGS (while dropping) are still relatively high and thus minimizing non-specific amplification will likely be prioritised accordingly. While the post-QC number of sequences are in many samples comparable between primer pairs, please present (in the text) any differences in the quality of the sequencing between primer pairs (check for any patterns in depth vs number of reads that pass QC).
Furthermore, whilst this information is likely contained in previous publications (Hume et al), it should be briefly discussed HOW this primer pair has achieved its superiority. I.e. differences in the region of binding, the degenerate design, etc, are currently missing from this manuscript.
Additional comments: Minor comments:

142 –Is there already a DOI or deposit number for the Pangea database that can be referenced here?
161 – Check the reference formatting and spelling of author names.
203 – Change spelling to Mothur
236 – Why this e-value? This seems very high. First interpretation of this value is that we would expect 50 matches to occur simply by chance? Please clarify the use of this threshold.
260 – Which manufacturer? Of the PCR reagents?
275 – Check spelling. “cycle number, OR annealing temperature”.
281 – Please provide some coefficient of variation for these % values here, and throughout the results section.
286 – Does this “respectively” refer to the previous paragraph?
381 – For samples where you only recover 3 out of the 9 known clades, which is a low diversity compared to what is recently being described from reef sediments (7+ clades, Quigley et al 2017 Frontiers), there are only limited conclusions you can draw related to intra-cladal bias. You do suggest the conservative approach, that 56 C is the better option given the small potential for bias, but it should be discussed how further optimisation and assessment of intra-cladal bias need to be carried out on either artificial communities or natural communities with a greater intra-cladal diversity.
387 – This is not what you stated you would do. Above you state you will increase the number of cycles.
417,18 – This statement requires some supporting citation. As you mention, formal species descriptions thus far make limited use of the ITS2 marker or of its intragenomic variants. It is not clear for which clades or sub-clades ITS2 represents a true super-species, species, or sub-species level marker. At this stage species level descriptions have not developed beyond the requiring of other makers in support of the ITS2 data, including 28s, cp23s, and psbAncr.
Figure 1 and 4 – While the data within each panel are clear, they are displayed with an inefficient use of space and could be reformatted accordingly.
Table 2 – There appears to be an extra annealing temp value in line with ITS-DINO/ITS2Rev2
Table 3 – Please increase the decimal places on the chim/total column (or remove this column) as you already have the chimeric seq number in the table and some are clearly non-zero.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: AN IMPROVED PRIMER SET AND AMPLIFICATION PROTOCOL WITH INCREASED SPECIFICITY AND SENSITIVITY TARGETING THE SYMBIODINIUM ITS2 REGION
Review round: 1
Reviewer: 2

Output:
Basic reporting: The authors explained clearly the purpose of this paper and the language used was clear. The structure of the article generally speaking is professionally made.  A few references are missing but this is a very easy fix.  I have added comments on the pdf file.
Experimental design: The research question is very relevant as the question of which primers perform the best under the conditions that the authors tested would attract attention from the increasing number of people assessing Symbiodinium diversity.  However, I have explained in the test that I have detected some serious flaws in the experimental design; namely the missing info on the species names and the very low number of replications per potential species. The genomic part is commendable except that some details are missing such as the PCR machine used for the initial amplifications.
Validity of the findings: I have explained on the text that lack of basic information regarding the taxonomic ID of the corals and hydrocoral species and the very low number of individuals per species is limiting the potential value of this contribution.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: AN IMPROVED PRIMER SET AND AMPLIFICATION PROTOCOL WITH INCREASED SPECIFICITY AND SENSITIVITY TARGETING THE SYMBIODINIUM ITS2 REGION
Review round: 2
Reviewer: 1

Output:
Basic reporting: The authors have sufficiently addressed my concerns with the previous version of the manuscript and I recommend that it is accepted for publication.
Experimental design: The authors have sufficiently addressed my concerns with the previous version of the manuscript and I recommend that it is accepted for publication.
Validity of the findings: The authors have sufficiently addressed my concerns with the previous version of the manuscript and I recommend that it is accepted for publication.
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: FINDING NOVEL RELATIONSHIPS WITH INTEGRATED GENE-GENE ASSOCIATION NETWORK ANALYSIS OF SYNECHOCYSTIS SP. PCC 6803 USING SPECIES-INDEPENDENT TEXT-MINING
Review round: 1
Reviewer: 1

Output:
Basic reporting: The paper presents a novel and advanced proof-of-concept text-mining pipeline to develop information-rich gene-gene association network for model organisms. The proposed method to improve the accuracy of predicting genetic interactions and identifying novel interactions based on species-specific experimental data integrated with text-mining networks is exciting and useful at the same time. However, there are several key concerns which need careful attention from the authors.
Experimental design: The rationale and advantages behind identifying relationships in a triad pattern could have been elaborated and presented in a better way, because in addition to triad motifs, other motifs have been shown to be used in the literature [1, 2].

1.	Kashtan N, Itzkovitz S, Milo R, Alon U: Topological generalizations of network motifs. Physical review E, Statistical, nonlinear, and soft matter physics 2004, 70(3 Pt 1):031909.
2.	Milo R, Shen-Orr S, Itzkovitz S, Kashtan N, Chklovskii D, Alon U: Network motifs: simple building blocks of complex networks. Science 2002, 298(5594):824-827.
Validity of the findings: The ranking of the identified patterns seems straightforward; however, it will enhance the inclusion of possible incorrect motifs, and thereby increasing the number of false positives. It seems that being more conservative in accepting the multiple sources of existing knowledgebase is critical. Would the authors include quantitative information on the accuracy of these ranked patterns?
Additional comments: 1.	The authors should invest further care in rectifying a number of spelling issues throughout the manuscript (for example, page 12, line 271 reads “…Synechocysis 6803…”.

2. 	Labels (A) and (B) are missing from figure 2.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: FINDING NOVEL RELATIONSHIPS WITH INTEGRATED GENE-GENE ASSOCIATION NETWORK ANALYSIS OF SYNECHOCYSTIS SP. PCC 6803 USING SPECIES-INDEPENDENT TEXT-MINING
Review round: 1
Reviewer: 2

Output:
Basic reporting: In addition to Cyanobase, CyanoEXpress and STRING the following references are relevant to the current work

A database on regulatory interactions in cyanobacteria (RegCyanoDB, corresponding article on bioRxiv): https://www.che.iitb.ac.in/grn/RegCyanoDB/

A recent protein-protein interaction network in cyanobacteria: Lv Qi et al. Scientific Reports volume 5, Article number: 15519 (2015).  https://www.nature.com/articles/srep15519

L76-77: This sentence is not clear. How is the network expanded? What does “network depth” refer to? The likelihood of making correct predictions (i.e. accuracy) decreases … because of decrease in accuracy.

L80: Please point out in the introduction (and possibly the abstract) that the text-mining is performed on articles in PubMed Central. Can you provide an estimate of how large a fraction this is of all available (relevant) literature?

L282: Using abbreviations (GBA) in figure captions makes life more difficult for the reader. I suggest using replacing GBA by “guilt-by-association” in subsequent figures.

L320: Define abbreviations when they first appear. Using “key gene” and “candidate genes” makes the text more readable than using KG and CGs.

L324-343: This appears to be mostly repetition from the methods section.

L351: “Utility 1” -> The first case.

L500: “Uniquely present in some but not all“ ???

L598: Some of the references are missing/incomplete. E.g.  Hui et al. is missing and Kaewphan et al. 2012 and Hakala Kai et al. 2013 are incomplete. Please check the reference section carefully.

Figure 1: This figure does not provide much additional information to what is already stated in the text, in terms of number of publications, E. coli > A. Thaliana > cyanobacteria > Synechocystis. The figure is somewhat trivial and no harm would be done if it were to be omitted.

Figure 2: The caption “species-independent text-mining …” states the obvious. When comparing panels A and B it is not clear that “the same layout was used in both cases”. With ~800 nodes and ~3000 edges the graphical representation of the EVEX network in panel A is not informative. Most of the edges are buried behind the cluster of nodes in the center, which means that the “types” of most connections cannot be inferred from the figure. Omitting this figure would do no harm. The figure in panel B would be more informative if gene IDs were included (the network is probably small enough for this to be reasonable).

Figure 3: It might be worthwhile to highlight the slr1843 node.

Figure 5: The size of the blue circles indicates that the article count is the same for almost all the species other than E. coli. A scale for the event and article counts should be added.

Figure 6: Preserving the network layout between panels A and B would help with comparison.

Figure 7 (and others): What do the loops indicate?
Experimental design: Methods section
----------------------
L135-177: The construction of the “EVEX” network is difficult to follow. Was a list of genes from Synechocystis plus a list of genes from organisms from the same family (derived used as input to EVEX which then returns a network (list of nodes and edges)? Maybe some of the text in L254-261 should be incorporated here.

L185: Cyanobase had a significant update in Nov 2016, including annotation updates. What is the reason for using a Cyanobase version from 2012 in this work?

L109: How was the correlation threshold of +/- 0.7 chosen?

L114: “EVEX” refers to a database, a pipeline and a network in the manuscript. Please clarify.

L114: Please motivate the selection of EVEX for the text-mining task. What about using e.g. BioContext (Gerner et al. Bioinformatics. 2012 28(16):2154-61)? You might want take a look at the text-mining effort of Westergard et al. (bioRxiv Jul 11, 2017.  http://dx.doi.org/10.1101/162099) which includes articles from Springer and Elsevier as well as PubMed.

L149: The folP and MiaB example is not very helpful.

L155: The network*s*?

L181: Giving the merged network an identifier here (INTNET?) would make it easier to refer to it later on.

L189: The rule-based algorithm is referred to as a rule-based script, rule and pattern-based script, rule-based filtering scripts, automated script, … which is confusing. Please stick to a single term. What about referring to the procedure simplify as a filter?

L190: Please define the “guilt-by-association”. The description of how GBA networks are constructed is confusing. How do you extend a network by adding neighbors to the nodes in the network (where do the neighbors come from?)

L193: Please explain why the triad motif is relevant in this study (three different data sources?) Would it be meaningful to use other motifs? How would you expect the results to change if other motifs were to be used?

L207: “The script” becomes two scripts in L211-213.

L237: Since the number of articles on E. coli in PubMed is approx. 100 times greater than the number of articles on Synechocystis (L54-55) extrapolating accuracy figures from a previous E. coli study to the present Synechocystis study is at best optimistic.
Validity of the findings: L316: Please provide a comparison with the most recent version of Cyanobase (or if that is the case, please update the reference to Fujisawa et al. 2017).

Since there is no experimental validation of the predictions, the use of the method as a "hypothesis generator" should be highlighted.
Additional comments: The authors describe a method for discovering gene-gene relationships by combining experimental data with literature mining. The method may turn out to be useful for studying relatively unknown species, providing an alternative to simple homology search.

The authors provide several case studies demonstrating the use of their methods but without independent (experimental) verification it is not possible to assess the accuracy of the predictions. Case study 6 is particularly interesting since it demonstrates how the method can be used to study hypothetical or unknown genes.

Some parts of the manuscript are difficult to follow and terminology needs to be clarified. Examples and suggestions on how to improve them are given.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: FINDING NOVEL RELATIONSHIPS WITH INTEGRATED GENE-GENE ASSOCIATION NETWORK ANALYSIS OF SYNECHOCYSTIS SP. PCC 6803 USING SPECIES-INDEPENDENT TEXT-MINING
Review round: 2
Reviewer: 1

Output:
Basic reporting: No further comments
Experimental design: The reviewer's comment has been addressed.
Validity of the findings: The reviewer's comment has been addressed.
Additional comments: The reviewer's comments have been addressed.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: FINDING NOVEL RELATIONSHIPS WITH INTEGRATED GENE-GENE ASSOCIATION NETWORK ANALYSIS OF SYNECHOCYSTIS SP. PCC 6803 USING SPECIES-INDEPENDENT TEXT-MINING
Review round: 2
Reviewer: 2

Output:
Basic reporting: .
Experimental design: .
Validity of the findings: .
Additional comments: The authors have addressed all my previous comments in a satisfactory way and I can now recommend the manuscript for publication.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A BRIEF INTRODUCTION TO MIXED EFFECTS MODELLING AND MULTI-MODEL INFERENCE IN ECOLOGY
Review round: 1
Reviewer: 1

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: The review summarises the best practice and recommendations for ecologists conducting LMMs and GLMMs. Of course, we have a wonderful paper by Bolker et al (2009; Trends in Ecology and Evolution) but this was nearly 10 years ago and we probably need an update. I think this manuscript is a very approachable paper from which practicing ecologists can learn. I like seeing my good references written by ecologists which makes this paper really relevant to the target audience. I have several relevant references the authors.

Lines 104 and Line 346. The authors may have missed this paper:

Warton DI, Lyons M, Stoklosa J, Ives AR. Three points to consider when choosing a LM or GLM test for count data. Methods Ecol Evol. 2016;7(8):882-90.

Line 594. There is a recent paper

Nakagawa, S., Johnson, P. C. D. & Schielzeth, H. (in press) The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded. Journal of the Royal Society Interface (BioRxiv. doi: https://doi.org/10.1101/095851)

Line 640. There is a very useful simulator for ecologists and evolutionary biologists called SQuID

Allegue H, Araya-Ajoy YG, Dingemanse NJ, Dochtermann NA, Garamszegi LZ, Nakagawa S, et al. Statistical Quantification of Individual Differences (SQuID): an educational and statistical tool for understanding multilevel phenotypic data in linear mixed models. Methods Ecol Evol. 2017;8(2):257-67.

Lines 698 Murtaugh has several good papers on this topic. The latest I believe in this special issue.

http://esajournals.onlinelibrary.wiley.com/hub/issue/10.1002/ecy.2014.95.issue-3/

This relates to the next section of model selection as well.

Line 834

I wondered why the authors did not talk about DIC? (known to be not great for GLMMs although probably works for LMMs).

Line 887

Galipaud M, Gillingham MAF, Dechaume-Moncharmont F-X. A farewell to the sum of Akaike weights: The benefits of alternative metrics for variable importance estimations in model selection (online early). Methods Ecol Evol.


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A BRIEF INTRODUCTION TO MIXED EFFECTS MODELLING AND MULTI-MODEL INFERENCE IN ECOLOGY
Review round: 1
Reviewer: 2

Output:
Basic reporting: This paper provides an overview of methods and considerations in the use of mixed effects modelling in ecology. This is a timely subject, and likely to be of use to many readers. Overall I found that the paper contained many useful tips and suggestions. I have provided a number of comments that I believe could improve the utility and rigor of the paper.

One of my main concerns was a lack of cohesion amongst the topics.  The paper seems as though the authors have attempted to cover too many issues, and as a result the most topics are covered only superficially (many of the topics are covered in greater detail in other reviews, which the authors cite), and the connections between topics are weak. Thinking about the title and objectives of the paper, I felt that the paper would be strengthened by a greater specific focus on considerations around random factors and apportioning and interpretation of error. For example, I thoroughly enjoyed reading the first half of the paper (up to L275) but felt more and more unsure of the goals of subsequent sections. For example,
• The section “choosing error structures and link functions” is too long, as much of this material is well covered by other reviews, and the considerations noted are not necessarily dependant on whether a research runs an LM or LMM.  Focussing the current review on just a brief description of link functions, followed by a more detailed consideration of the impact of random factors on link function choice (if any), would be much more valuable.
• Similarly, the section “choosing predictors and interactions” misses an opportunity for a more in-depth discussion of decisions around which random factors to include – for example I found little guidance for researchers on how to make decisions about “nested” random factors, or how to decide whether it is appropriate to use multiple random factors additively (how is the error then distributed?). This section could be assimilated with the section “how complex should my global model be?”.  Many of these issues are also relevant to the section “using the nesting rule to improve inference from the top model set” – how should researchers consider their use of random factors when thinking about model nesting?
• The section “assessing predictor collinearity” makes no mention of random factors at all, which is surprising given their primary importance to the paper (in the title), and the fact that researchers may wonder what to do about collinear random factors.

Some additional general suggestions for improvements:
• Around L470 would be a good place to comment on the impact and management of missing data, with particular reference to missing data amongst fixed versus random factors.
• Section “standardising and centering predictors” – this approach can also be considered as a transformation of the predictor variables, and so might be best if shortened and assimilated with the material at L294-301.
• L852 “at least delta-6 is required to guarantee a 95% probability…”, actually the use of a 95% confidence set, as described at L855 is the best way to guarantee 95% probability – I would suggest that choosing a delta cut off versus using sum of Akaike weights represent two different approaches to determining the final set.  What is meant by a “cumbersome” (L856) top set, and why is this a problem?
• L942 “reversible jump MCMC” here in the last line of the paper is the first mention of this technique! I suggest providing more detail elsewhere, if it is relevant, or removing from the conclusions.

Overall the paper is well written, however I found the tone to be a informal in places. Specifically, the paper is written in the second person in many places, which comes across as prescriptive rather than informative, and is mostly unnecessary for statements that are not addressed to an individual. For example,
• L356 “you can’t transform a 0” should be “zeroes cannot be log transformed”,
• L483 “where you subtract the mean…” should be “where the mean is subtracted”.

The literature is well referenced and relevant.

The figures are of high quality and appropriate.
Experimental design: I appreciated the use of simulations to test some of the ideas being put forward.  The text indicates at L662 that the R-code used to generate the simulations is available as online supplementary material, however I was unable to find this file amongst the review documents and therefore unable to confirm that the code runs as expected.

A L869 the authors “…suggest delta-6 as a minimum following Richards…” – but the authors conduct simulations to determine the false positive rate of only delta-6, why not also investigate delta-2, which is also commonly used, and then use the empirical evidence to support their qualitative arguments?

Considering the simulations, I’m not convinced that it is appropriate to use information theory to rank and compare models, and then using null-hypothesis testing to consider the significance of predictors and draw conclusions about the likelihood of type I error.  Unless I am misinterpreting the methods, this seems to be mixing statistical paradigms in a way that many users would find inappropriate. Better would be for the authors to follow the advice put forward in the paper and use measures of model quality such as R2 to determine whether delta-6 (or any other delta value, see my comments above) provides the “best” model fit of their data. I would particularly like to see the impact that random factors have on the outcomes, given the objectives of the paper.  Looking at the simulation methods, only one type of random factor was used “the random effect was always a six level factor in continuous blocks of random length”.  Why not simplify the fixed factors, and experiment with single or multiple random factors, nested or unnested random factors, different types of response variables (and thus different link functions)?  Taking this approach would enable the simulation material to quantitatively support many of the recommendations made in the paper.
Validity of the findings: While the paper collates some good recommendations from the literature, I found that a few recommendations need more evidence to be convincing. Some of this may come from greater use of the simulation study (see above). For example,
• L421 “good rule of thumb” – by what measure is it “good”? Is this rule proposed here for the first time (on what evidence?) or by others (provide citation). Is it plausible that this may not be a good rule in certain circumstances?
• L432 “…ideally >100” – what is this figure based on?
• L463 “…potentially arbitrary choice…” – why is it arbitrary? What is the choice typically based on? What should the choice be based on?
• L510-512 “often, researchers…claim that the large difference in AIC between the top and null models is evidence of a good fit” – do the authors have evidence that this practice is common?
• L557 “…can ‘fix’ the overdispersion…” – how/why?
Additional comments: No additional comments


Instruction: You are one of the reviewers, your task is to write a review for the article. You will be given the title of the article, the number of the round in which the article is located, and your order among the reviewers.

Input:
Title: A BRIEF INTRODUCTION TO MIXED EFFECTS MODELLING AND MULTI-MODEL INFERENCE IN ECOLOGY
Review round: 1
Reviewer: 3

Output:
Basic reporting: largely okay to good (language, structure, self-containment); some  references are under-appreciated (see detailed comments to authors)
Experimental design: doesn't really apply. The simulations are well designed but their evaluation misses a few points (see detailed comments to the authors).
Validity of the findings: doesn't really apply. However, the findings of the simulations seem valid (but their evaluation should be changed; see my detailed comments to the authors).
Additional comments: General comments

This manuscript gives an overview abouut two concepts/approaches that rapidly gained popularity in applied statistics during the past decade, namely mixed models (GLMM) and multi-model inference (MMI). The authors give a broad overview and treat a couple of issues coming along with the use of GLMM and MMI. Overall, I feel very sympathetic about the authors' intention to formulate 'best practice' guidelines for users of these approaches since more guidance as to how to use GLMM and MMI appropriately in ecology, animal behaviour, etc. is definitely needed. I also feel that the authors managed to cover the more recent literature fairly well and to write in a style which will be accessible to most scientists, also those not very familiar with statistical jargon.

However, I also feel that the goal of the article is too ambitious to be met. First, GLMM and MMI have in common that they only fairly recently became more popular and that they are based on maximum likelihood fitting, but apart from that there is not really much of a relation between the two approaches (as can be also seen in the manuscript). Hence, I feel the manuscript could benefit (perhaps a lot) by splitting it into two. This would allow for each of the two topics to be treated more in-depth, which, at occasions, would be highly desirable. In fact, as off now, the manuscript treats several crucial issues quite briefly (too briefly, in my view; see below for details). Second, the title ('Best practice...') sets the level very high, but the manuscript then quite frequently remains fairly vague and does not go much beyond mentioning open questions (examples are, e.g., random slopes or the choice among AIC and BIC; see below). In parts, this is not surprising (and probably the most and best the authors can do) since GLMM as well as MMI are both methods which currently are subject to developments and improvement as well as investigations of their properties (with sometimes surprising outcomes). As a consequence, our understandings of how to use and interpret results of GLMM and MMI have changed quite drastically over the past years (e.g., importance random slopes in GLMM or use of Akaike weights for predictors in MMI; see below). I myself use both approaches very regularly and frequently and feel fairly well on top of the current literature but still would not dare to formulate 'best practices' for either of them, feeling that they might be outdated in the near future and/or some would be matter of too much uncertainty and debate. (so regarding the title I'd feel beginning it something like 'A brief introduction to …' would probably be better suited than 'Best practices...'.). For further more detailed comments see also further below.

Apart from that the authors at occasions lack clarity regarding the topics they treat. This is the case in the section about LRT, minimal adequate models and stepwise model selection (see my comments re L 675-703); in the section about all subsets and dredging (see my comments re L 760-817); in the section about the simulation addressing the effects of dredging (see my comments re L 772-788); when the authors refer to model selection (see my comments re L 809-811; to some extent this refers to the whole section, i.e., L 666-744). One might argue these issues to be mere semantics, but in my view most of them reflect fairly important sources of confusion which need to be worked out way better in order to not make things worse than they currently are (and this is particularly important for everything related to model selection).

Some more issues I feel being important can be found in the specific comments below.

Specific comments

general: I missed a statement about model stability

L 80-83: well described/presented; but the authors do not address how these issues can be tackled...

L 131-133: do they really model variance hierarchically in the sense of sequentially? I believe to recall from the literature that all these effects are estimated simultaneously (i.e., each while controlling for the others).

L 110-140: somewhere within this section it should be mentioned that the whole question of whether to fit a predictor as a fixed or random effect is only one for *factors* (i.e., quantitative predictors are always modelled as fixed effects).

L 146-186: this whole section falls short of what we know (and don't know) and need to do with regard to random slopes. First of all, in my view, whether random slopes are to be included should not so much be determined by the 'goals of the analysis' (L 152) or what we 'wish' to know (L 158-168), but should be driven by the data structure and the desire to have unbiased standard errors and confidence intervals for the fixed effects and keep type I error at the nominal level (of, e.g., 5%). In fact, there is now ample evidence that neglected random slopes can lead to drastically inflated type I error rates (see, besides Schielzeth & Forstmeier 2009, e.g., Barr et al. 2013. Random effects structure for confirmatory hypothesis testing: Keep it maximal. J Memory Lang, 68, 255-278; or Aarts et al. 2015. Multilevel analysis quantifies variation in the experimental effect while optimizing power and preventing false positives. BMC Neurosci, 16, 94). At the same time there are now articles emerging that recognize difficulties and potential disadvantages coming along with the use of such 'maximal models' (see, e.g., Matuschek et al. 2017. Balancing Type I error and power in linear mixed models. J Memory Lang, 94, 305-315; or https://arxiv.org/abs/1506.04967). So, rather than formulating 'best practice' (which, in my view, would be to generally consider random slopes), this section simply mentions the existence of random slopes and explains what they model. But it neglects that random slopes play a central role when wanting to infer about the relevance of fixed effects; and it misses the ongoing debate about them and the potential problems a maximal model can cause with regard to inference about random effects (and perhaps power for the fixed effects, too).

L 188, 206, 234: I found these headers kind of odd ('To …').

L 212: wouldn't one consider the intercept to be a fixed effect, too?

L 270-272: this second example I didn't understand.

L 232: I would not say that the transformation of the linear predictor 'normalises the residuals of the model', and I also don't really understand this statement.

L 353: I'd mention which assumptions need to be checked.

L 355-358: I was surprised to read this. What I see most frequently is that a constant (i.e., the same value) is added to *all* values.

L 408-411: it is not even possible to fit a model comprising 'more parameters than observations'. At the same time a model can also be overparameterized when it comprises fewer parameters than observations (see Box 8.3 in Quinn & Keough).

L 421-424: this rule of thumb I didn't understand at all. Failing in which sense?

L 436-437: I would be a little cautious with referring to the paper by Zuur et al. In the context here largely because it doesn't make at all clear that the practice they recommend for determining which interactions to include means to conduct an exploratory data analysis with all its consequences (elevated type I error rate, biased P-values, SE, and confidence intervals, etc.).

L 445: I'd say collinearity *among*.

L 457-462: In my few, VIF are to be preferred over correlations since heavy collinearity can come in forms undetectable when using correlations (that is, one should always inspect VIF). Also, there is a multitude of thresholds mentioned for VIF being critical (see, e.g., Quinn & Keough 2002 which mention a value of 10).

L 462-469: the solutions mentioned do not solve the problem of the arbitrary threshold.

L 468: a single or few.

L473-478: this is pretty imprecise. The 'outcome' mentioned is one of a PCA or FA but not of a model with two collinear predictors; and the mere fact that two variables 'share contribution to a principal component' cannot be 'taken as strong indication that the predictors’ signal cannot be teased apart'. In fact, it is a common misinterpretation that two variables having somewhat larger absolute loadings on a principal component must be strongly correlated.

L 443-478: this whole section does not mention at all how one would check for collinearity in a GLMM framework. This would be interesting to be treated since many users of GLMMs are concerned about collinearity between fixed and random effects, and because the R functions I am aware of cannot be applied to GLMMs.

L 489-490: when the main effects are covariates, or?

L 497-498: how could scaling improve the robustness of a model? The model is actually virtually identical (but the coefficients get another interpretation).

L 507-508: I don't see the link between model fit and robustness (a model can have a poor fit but be robust, e.g., in the sense of not suffering from instability; and a model can also show a very good fit but not be robust, for instance due to model instability or overfitting).

L 521: 'non-linear effects of the predictors on the response' to be precise.

L 526-528: but the inspection of residuals vs. fitted values only makes sense for Gaussian models, or?

L 534: 'means' rather than 'modes'?

L 536: random effect 'residuals' or rather 'means' ('BLUPs'; see Baayen RH. 2008. Analyzing Linguistic Data. Cambridge University Press. Cambridge).

L 551-553: overdispersion affects standard errors but *not* the estimates (Gelman A & Hill J. 2007. Data analysis using regression and multilevel/hierarchical models. Cambridge University Press. Cambridge; P 115).

L 657-663: this seems like an excessively complex way of examining absence of overdispersion. Why not taking the dispersion parameter of 3.16 as conclusive evidence of strong overdispersion?

L 695-699: Mundry (2011) is actually arguing against model simplification

L 691-694: I would say that the most important source of unreliable LRT of fixed effects in GLMMs are neglected random slopes (see my comments above).

L 675-703: this para mixes as couple of, at best, loosely connected topics. One topic treated is selection of a MAM, and, as shown by, e.g., Mundry (2011), this likely leads to greatly inflated type I error rates if the model or the terms it comprises are then tested using NHST. The, in my view, most important question is as to when to even consider an MAM? For testing it leads to greatly inflated type I error rates (Forstmeier & Schielzeth 2011; Mundry 2011) and I only see its value when it comes to making predictions. Another topic treated is stepwise model selection (as one method of coming up with an MAM; there are others), and this has so many times been shown to be useless that I don't see what else can be said about it rather than it being useless (see also Mundry & Nunn. 2009. Stepwise Model Fitting and Statistical Inference: Turning Noise into Signal Pollution. The American Naturalist, 173, 119-123). In between the authors briefly touch on the reliability of LRT for fixed effects in GLMMs (see my comment re L 691-694). And yet another topic is NHST itself (which could be contrasted with information theoretic or Bayesian inference). So I think this para is not helpful as it is. First, the authors need to decide which topic they want to address, and then they should focus on this topic.

L 719: I'd say 'similarly' rather than 'equal'.

L 749: I wouldn't label this approach 'conservative' but simply one which produces nominal type I error rates.

L 754-756: here the authors mix NHST and inference based on an information criterion which should never, never, never, be done. In fact, just browsing the book for statements written in bold, one can find several statements strongly arguing against using words such a 'significance' in the context of an IT analysis; and Mundry 2011 clearly showed that selecting a best model using AIC and then considering its significance or the significance of the predictors it comprises leads to greatly inflated type I error rates. Hence, such practice doesn't have any merits, and should clearly argued against.

L 760-817: this whole section is somewhat unclear in the sense that 'all subsets' and 'dredging' are conflated: 'all subsets' refers to how the set of models considered is constructed whereas 'dredging' refers to what is done with the results revealed for multiple models. The authors are correct that Burnham and Anderson (2002) repeatedly and strongly argued against 'all subsets' (but at the same time they report at least one such analysis in their seminal book); but others have been more relaxed about this (see, e.g., Box 2 in Stephens PA, Buskirk SW, del Rio CM. 2007. Inference in ecology
 and evolution. Trends Ecol Evol, 22, 192-197). So in my view, no simple statement can be made regarding whether an 'all subsets' is advisable or not. 'dredging', in turn, refers to an analysis during which a couple of models (which may or may not have been 'all subsets' of a full model) have been fitted and inference is then drawn on some 'best' model (selected using stepwise or based on an information criterion) or simply the most (or only) significant one identified by a researcher. So these two topics are only loosely linked and the manuscript would benefit from the two treated separately.

L 772-788: this simulation conflates three issues: model selection and subsequent testing (as has been addressed by Mundry 2011); cryptic multiple testing of multiple predictors in a single model (as has been addressed by Forstmeier & Schielzeth 2011); and neglecting to test the contribution of a factor with several levels before considering pair-wise comparisons (see 'testing sets of variables' in Aiken & West. 1991. Multiple Regression: Testing and Interpreting Interactions. Sage. Newbury Park; or Cohen & Cohen. 1983. Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates, Inc. New Jersey). All three issues lead to inflated type I error rates and the simulation doesn't tease these effects apart. So I think this simulation is not very helpful.

L 789: I think dredging should simply not be used.

L 801-802: one model to represent all hypotheses simultaneously, or one model for each of them separately? In the former case I would not see much of a need of applying any model selection at all...

L 804-809: here the authors should be careful: after having conducted a full-null model comparison sensu Forstmeier & Schielzeth (2011) this would no more represent dredging; but without a preceding  full-null model comparison this would be dredging with all its adverse consequences (inflated type I error rate and effect sizes, etc.).

L 809-811: useful for which purpose? Here the authors stand on weak philosophical grounds. The first and most important question to be asked when it comes to model selection is 'what is it used for?' Model selection for inference and model selection for prediction are two very frequently confused but very different issues with very different implications and dangers. Here the authors are not clear about what they refer to and I fear they do not know either. So this needs to be reworked after it has been clarified what purpose (inference or prediction) the model selection serves.

L 848: why does model averaging 'require the identification of a “top model set”'? Its one of the beauties of this approach that one can simply average across all models (and models with little support then would have little impact on the model averaged parameters)... This has impact for the rest of the paragraph which actually seems rather addressing the question of how to draw inference in an MMI framework.

L 854-857: what is the problem with a 'cumbersome' top models set? It basically means that there is not a single of a few models that stick out from the rest – which, in my view, would be an important finding in itself.

L 874-877: I don't really see the problem here: the models are dropped from the set and then one recalculates Akaike weights. Or do I miss something here?

L 882-887: in this context two recent articles might be worth considered:
Galipaud, M., Gillingham, M.A.F., David, M. & Dechaume-Moncharmont, F.X. 2014. Ecologists overestimate the importance of predictor variables in model averaging: a plea for cautious interpretations. Methods in Ecology and Evolution, 5, 983-991.
Galipaud, M., Gillingham & Dechaume-Moncharmont, F.X. 2017. A farewell to the sum of Akaike weights: The benefits of alternative metrics for variable importance estimations in model selection. Methods in Ecology and Evolution, in press.
Both seem to have the potential to drastically change our assessment of the value of Akaike weights for inference about predictors.

L 925: fishing expeditions *are* very risky.