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: FINE-SCALE DIFFERENTIATION BETWEEN BACILLUS ANTHRACIS AND BACILLUS CEREUS GROUP SIGNATURES IN METAGENOME SHOTGUN DATA
Review round: 1
Reviewer: 2

Output:
Basic reporting: A clear, unambiguous, professional English language was mostly used throughout.
I highlighted specific cases where I could imagine that appropriate rephrasing would benefit the readability of the paper.
The intro & background show the necessary context and refer to the relevant literature.
I have not checked whether the word counts are followed but leave this up to the journal to verify. The structure appears to conform to PeerJ standards.
The figures are relevant, high quality, and well labeled.
While for the main figures the respective captions were given, I could not find the captions of the Supplementary Figures.
Raw data has been supplied based on a high-level check. I have not been able to check all details.
The availability of an Rmarkdown based notebook on Github is commendable.
Experimental design: The original primary research presented in this work is within the scope of the journal.
The research question is well defined, relevant & meaningful. It is stated how the research fills an identified knowledge gap.
Rigorous investigation was performed to a high technical & ethical standard.
The methods are described largely with sufficient detail, please also see my general comments for cases which could be improved. While I have not attempted to fully replicate the findings based on the information available, the authors appear to have followed very good practices by using version control (via Github) and provide an Rmarkdown file including code.
Validity of the findings: The data appears robust, statistically sound, & controlled
The conclusions are well stated, linked to the original research question & limited to supporting results.
Additional comments: SUMMARY
Petit et al. present an interesting study on the identification of biothreat-derived sequences from metagenomic data, focused on the biothreat agent Bacillus anthracis.
The authors investigated possible sources for errors in the taxonomic assignment of metagenomic samples. In order to overcome these errors, the authors propose a gene-based (i) and a genome-wide (ii) approach to predict the presence of pathogenic species, as well as a sequencing-coverage dependent model (iii) to reduce the likelihood of false-positive B. anthracis assignments. Moreover, the authors reanalysed data from a study which was strongly and openly discussed in the scientific community and for which respective corrections were originally performed. The present work further supports this and it is commendable that the authors did it in this structured and extensive way.
The manuscript is overall well written. However, I was lost sometimes (indicated in my general comments below) and I think that the authors should try to improve these parts of their manuscript in order to improve its readability.

GENERAL COMMENTS:
1. L20: "small phylogenetic distance and both the pathogen and non-pathogen species are
present in the same sample". I am not sure about the use of "phylogenetic" distance in this context. While I understand what the authors mean, a species may become pathogenic with the acquisition of only a few genes, yet, the phylogenetic distance would be extremely small, maybe even zero. Moreover, it depends on which _gene_ is used to define the "distance": In case of one of the acquired pathogenicity-related genes, the distance would be large. This could be rephrased to reflect a rather evolutionary perspective, maybe.
2. L27: "we identified 31-mer signatures that differentiated B. anthracis from other members of the B. cereus group (BCerG), and from 31-mers conserved in all BCerG genomes (including B. anthracis), but not in other Bacillus strains". This sentence should be rephrased for clarity, e.g., "[...] and we identified 31-mer signatures that differentiated BCerG genomes from other Bacillus strains", given that I correctly understood the original intention of the authors here.
3. L73: "ANI (average nucleotide identity)". Isn't it a convention to first write the text out before introducing the abbreviation? The authors did so at least for the k-mer sets in the abstract. Maybe this could be adjusted accordingly.
4. L88: "Plasmids from other BCerG genomes may be very similar to pXO1 and pXO2, but lack the important virulence genes." Is this a speculation or do the authors have a reference for this? If so, please include it as concrete examples of this would further support the importance of the authors' work.
5. L113: Could the authors please explain the use of "NOT txid86661[Organism:exp]", i.e., why were B. cereus genomes excluded here?
6. L141: "from from"
6.1. L152: While this is clearly a debatable point, I was wondering why did the authors include Suppl. Fig. 1 into the Supplements instead of the main text? I think this information can help the reader to more readily understand the individual steps. Moreover, I think that the k-mer set names, e.g., Ba31, could be included as output of the workflow to link this better to the manuscript text.
7. L184: Were the simulated reads error-trimmed or pre-processed somehow? I am not sure about how ART simulates the reads, but Illumina sequencers are know to have an increasing drop in quality (and hence increase in the error) towards the end of the reads. The number of erroneous k-mers would thus also be expected to increase towards the reads' ends.
8. L185: I understand that a certain model had to be fixed here. Could the authors please elaborate on why the HiSeq2000 error model was chosen? Was it the "most recent" one available in ART? Is it assumed that the HiSeq2000 is the most common sequencing instrument? How about newer Illumina machines? Depending on the amount of extra work for this, it might be good to compare the performance of the k-mer sets on the HiSeq2000 error model with the performance on NextSeq500, for example representing a newer Illumina machine.
9. L189: How about "precision"? Moreover, the authors refer to these performance metrics but seem to not use them later in the manuscript, at least not in their mathematical sense. I would suggest revising this accordingly.
10. L194: Please also report the R version and version of the base stats package.
11. L198: Does the title refer to "host-derived/environmental samples" as the text mentions "metagenomic mixtures"? If so, please include this in the title of L198.
12: L204: What is the reason for not using the k-mer set name "Ba31" here? I would find it more consistent to stick to these namings as much as possible throughout the manuscript.
13: L210: Please see my comment about L204.
14: L252: I could not readily see why "~0.18x" would be the cut-off. The highlighted fold-coverage in Fig. 1 do not match this number. As it seems to be an approximation ("~"), it would be good to specify the exact value at least once.
15: L257: I am unsure if I have missed something here. Because, while I understand what the authors mean here, from my reading of the "previous section", it was about the lef gene, not about B. anthracis chromosomal markers in general. I would hence suggest to rephrase this sentence accordingly or include results on chromosomal markers (beyond the plasmid-borne lef gene).
16: L271: I found this to be very interesting. It highlights the importance of taxonomic curation; in general but also within the context of this specific approach.
17: L276: It was not readily clear to me where the "coverage" comes from, i.e., which data is searched for the respective Ba31 and/or BCerG k-mers. Is it still the NYC subway metagenomic dataset? Or is it the 164 B. anthracis genome projects? Or is it the set described in L191 ff? This is a crucial point as the (linear) model performance is expected to be highly dependent on the training/learning of the model parameters. Please make this more clear.
18: L286: Is this shown somewhere, i.e, the results of non-BCerG genomes?
19: L292: While I understand the rationale for subsetting the BCerG strains to a clade that is different, yet most closely related to B. anthracis, I think that the emerging linear model is then somewhat misleading. Concretely, it is not clear whether the model will be applicable to BCerG in general, or rather to this specific clade. In case of the former, an initial "closeness check" would be needed to test if the conditions/assumptions of the developed model are fulfilled or not. Interestingly, the authors rightly state this in L308. I would suggest to emphasize this more strongly, potentially even in the Abstract.
20: L302: An "in" is missing -> "is shown _in_ Table 3 ..."
21: L349: I would suggest to also include the developed sequencing error model into the list of "outputs". Or is there a particular reason that the authors have omitted it?
22: L390: "is" is missing -> "It _is_ important ..."
23: L401: This reads a bit contradictory to me. If the k-mer set was _specific_ to B- anthracis, why would one expect the false positive calls to be due to common co-resident BCerG bacteria, rather than due to sequencing errors, especially in case of high-coverage B. cereus members? Please let me know, should I have missed something there.


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: FINE-SCALE DIFFERENTIATION BETWEEN BACILLUS ANTHRACIS AND BACILLUS CEREUS GROUP SIGNATURES IN METAGENOME SHOTGUN DATA
Review round: 1
Reviewer: 3

Output:
Basic reporting: Overall this is a good summary of the challenges and new methods that have emerged for delineating various strains of Bacillus, and provides a new framework for separating the closely related strains.  This manuscript is well-structured and provides useful tools for future work.

A few questions about the current manuscript include:

1)	They used the Mash distance to reclassify each Bacillus genome as B. anthracis (Mash distance <= 0.000687), non-anthracis BCerG (Mash distance <= 0.135333), or non-BCerG (Mash distance > 0.135333). But is the Mash threshold the best measure?  I am wondering if these results would change if the thresholds were targeted to specific regions of the genome, or the plasmids, and if this could improve the separation?
2)	They have built models on 100x100 reads, but can the newer 150x150 reads improve the resolution?  I know this would be a bit of work but it would give more staying power to the analysis since almost all reads today at 150x150, and it may help with resolution of the Ba strains.
Small issues:
1)	There is a missing period at the end of the first paragraph.
2)	Is their python script (subsample-ba-lod.py) and other tools used publicly available? I don’t see it in the Zenodo link (for which the authors are commended, BTW), since some of the links (ilke bam2fastq) are no longer viable, and/or have been deprecated for new tools (like Picard) from https://gsl.hudsonalpha.org/information/software/bam2fastq.
3)	The authors should also and the official correction from the journal: https://www.cell.com/cell-systems/fulltext/S2405-4712(15)00015-0.
Experimental design: Find as is.
Validity of the findings: An update to a hard question in species classification and useful sets of k-mer tools are set up as well.
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: UNVEILING COMMUNITY PATTERNS AND TROPHIC NICHES OF TROPICAL AND TEMPERATE ANTS USING AN INTEGRATIVE FRAMEWORK OF FIELD DATA, STABLE ISOTOPES AND FATTY ACIDS
Review round: 1
Reviewer: 1

Output:
Basic reporting: The manuscript is well written with sufficient literature references. I particularly liked the interpretation of the Wasmannia auropunctata result (high 15N, feces feeder) in the context of Davidson (2005).

Line 72: How ‘ecologically’ different are these species?
Line 74: Replace ‘evolutive’ with ‘evolutionary’
Line 213: How compartmentalized a community is.
Experimental design: Line 127-131: Please provide more ecological detail about the study sites.

Line 138: How does this method uniquely estimate ‘multidimensional nutritional niches’? Meaning unclear.
Line 140: It is frustrating as a reader to be referred to another paper for description of the methods used in the present study (this is a recurring theme throughout the methods). Please at least include these important details in a supplementary appendix here.
Line 143-145: Please provide more information about the pitfall sampling regime. How long were pitfalls left in the ground, and at what densities were they placed? And, how was this data used to ‘verify whether bait records represented well the epigeic community?’ Table 1 doesn’t provide enough information to assess methods or the sampling effort. Each bait type needs to be explained.
Line 149: why only this subset of baits?

Line 108-116 & 148-153: After these descriptions of the NLFA approach, it is still unclear exactly what the data mean and how they enable one to infer dietary niche breadth, and which aspects limit their utility in comparisons across species and sites. Perhaps it could help to integrate some of the detail currently developed in the Discussion (lines 403-473) in the context of hypotheses in the Introduction?
Additionally, given the newness of this technique to the field, it is not sufficient to refer the reader to the Rosumek study for the details in the Methods.
Line 151: redefine NLFA here.

Line 156: Aren’t ants stored in EtOH of limited utility for SIA analyses? Was any attempt made to verify the effects of the storage method on the results of isotopic analyses?
Line 160 (also 494-499): To what extent the SIA values presented here comparable across communities? Aren’t such values usually baselined relative to potential food resources (and plant material at the 1st trophic level) available in each community? Moreover, the underlying logic of using heavy isotope signatures to make ecological inference should be expanded upon (i.e. move some of the ideas from the Discussion [Lines 475-509] to the Introduction in the context of a priori hypotheses).

Line 179: where is the reference collection stored? And, how were the Solenopsis sp. morphospecies determined?
Line 182: Unclear why bait data were combined with pitfall data for analyses.
Line 184-186: Meaning unclear. How were expected proportions weighted? How would this influence the results?

Line 195 & Table 2: Table 2 needs information on the sampling units. Were 14 Camponotus zenon workers observed across a certain number of baits (how many baits were provided of each resource per site?) or from one colony on a single bait? How are these numbers comparable? Are these percents? If so, percents of what? How is a Shannon index generated for each species? Define d’… There is too little information here to clearly interpret these data.

Line 196-197: Please provide more details about how this was done and why.
Line 197-198: Is there some way to provide information about the amount of FAA variation that was observed within species? And how were means calculated across all the NLFAs?

Line 201: Is there some concrete evidence that this was a single colony?

Line 232-234: This methodology is unclear: ‘pi is the proportion of resource use ‘i’ by each species, or NLFA found its profile’… Please elaborate

Line 240: when was it described that total fat content was measured? How many individuals per species?

Line 240-241: What is the ecological relevance of an unsaturation index [i.e. other than ‘the sum of percentages of each unsaturated NLFA multipled by its number of double bonds, Line 240-241)]?

Line 243: what is the meaning of C16:0, C18:0, C18:ln9? For the uninitiated, it is not possible to understand what these numbers mean, why they were chosen for further analysis, and what they say about ant nutritional ecology.
Validity of the findings: General speaking, the methods were sufficiently difficult to parse, as to make the results extremely difficult to interpret (see comments above).

Line 287: The amount of background information provided about this method to this point, makes it exceedingly difficult to interpret this statement.

Figure 1: It is very difficult to make sense of these trees. Are the units on the Y axis comparable between Brazil and Germany? Perhaps it would help if the colors of the tips for c and d were somehow color coded by genus or some other a priori ecological/functional trait framework?
Additional comments: This paper tackles important questions of diet breadth and community structure, comparing a German and Brazilian site. It is laudable that this study pairs 3 methods (field observation, fatty acid analysis, stable isotopes) acknowledging that each has limitations, and that together they can provide a picture of an ant’s trophic niche. Additionally, the idea that fatty acid analyses may also help corroborate stable isotope analyses is exciting.

However, this paper was also frustrating to read. Specifically, it lacked a clear conceptual framework (e.g. the methods are not clearly framed within hypotheses in the Introduction), had ambiguous methodological details (e.g. sampling design & effort) and lacked well-developed figure/table captions. Additionally, the meaning of the NLFA’s and their ecological significance within and between sites was unclear, even after reading the extended section in the Discussion. This lack of detail made it very difficult to interpret the results.

In general, perhaps the Introduction can spell out more clearly the differences between the tropical and temperate sites—and why these sites are hypothesized to have differently assembled/functioning trophic niches. This is stated in quite general terms—but, it seems a mechanistic basis for the study could be more clearly outlined. Along these lines, the identity of the 7 baits (it is not sufficient to refer to the Houadria paper, Line 137), and the rationale behind them are unclear (e.g. line 132)? Each resource should be clearly linked to an a priori hypothesis, established in the Introduction. For instance, is it really surprising that ‘seeds and melezitose changed positions between communities’ (line 262-263), or that ants used sugars ‘indiscriminately’ in Germany, but not Brazil (lines 263-268)? Was this unexpected?


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: UNVEILING COMMUNITY PATTERNS AND TROPHIC NICHES OF TROPICAL AND TEMPERATE ANTS USING AN INTEGRATIVE FRAMEWORK OF FIELD DATA, STABLE ISOTOPES AND FATTY ACIDS
Review round: 1
Reviewer: 2

Output:
Basic reporting: The authors did a good job on basic reporting and providing their raw data. If it is possible to spell out at least one of the 3 acronyms used in the paper, that would be helpful.
Experimental design: I have three major issues with the experimental design:

1) Storing samples in EtOH changes their carbon signature, and as such shouldn’t be used or discussed. Carbon signatures in Drosophila were lowered with ethanol preservation (Sarakinos et al 2002). I understand that one previous study pointed out (without statistical support) that this not of concern for ants (Bluthgen et al. 2003), but this finding was based on a single temperate zone species and it’s unlikely to hold across all ants. I think this is especially concerning because you show differences in the tropical and temperate zone ants with respect to fatty acids. Why would you then expect that EtOH has the same effect on species from different regions. Without knowing more about this particular effect, I believe C data should be removed from the manuscript. Furthermore, no baseline data was provided, so authors can’t discuss trophic levels as they don’t know with which 15N value does their first tropic level start.

2) Fatty acids were extracted from the whole body, unlike stable isotopes which were extracted from ants after removing the gaster. How can those data be comparable, if you are analyzing chemistry of different body parts? Additionally you collected the ants for fatty acid analysis from the baits. Is it possible that the consumption of the baits changed FAA signature?

3) Overall methods need to be more detailed. No one can replicate this study by reading the methods. The authors are relying on the assumption that the reader is familiar with their recent publications, if not, one needs to download 2 separate publications and read their methodology. I understand you used the same set up, but couldn’t you at least provide some basic information to make the methods more useful.
Validity of the findings: I believe this is a valuable data set, which includes a novel approach, however my concern is that part of the results should not be reported or discussed, and some might not be comparable because of the sampling method (see experimental design for details).

It’s unclear why were particular NLFA chosen to be plotted and discussed in PCA (Figure 4). Specifically Figure 4b does not show the most abundant NLFA: C18:1n9, and it is even present in the tropics in high concentrations. Wouldn’t it be interesting to see if they correlate with the same bait preference in both temperate and tropical regions? I think you should add NLFA recorded in highest concentrations to your PCA, especially if they are recorded in both sites, for example C18:1n9,C16:0, C18:0,.

Lastly, authors conclude that using multiple methods provides a more comprehensive picture of resource use, which is not shown, especially if we look at the temperate data set. It remains unclear how did FAA contribute more to understanding what is going on with resource consumption.
Additional comments: Study by Rosumek et al. explores a topic of resource competition combining an impressive number of resources and techniques using an omnivorous taxon, which are usually underrepresented in studies on resource use. The study tests the difference between the temperate and tropical ant communities in resource use, stable isotope and fatty acid signatures. The authors do a good job of compiling both behavioral and chemical data from two different ant communities, and this kind of data makes this an interesting and novel study.

Minor comments:
L44-6 Correlated in what way? Please be more specific when describing the relationship
L50-51 “Temperate species had distinctive NLFA patterns that were not related to different
diets, but may be influenced by environmental factors” The wording here is problematic because in L44 you talk about NLFA being correlated with bait use. I’m assuming the L50 refers to trophic position of the ants? However, this needs to be clearly stated.
L61-61 This sentence was already used in the abstract – please re-word
L78 Clarify what you mean by environmental mechanisms of coexistence
L81 This is not completely true see Davidson 2003, Bluthgen et al. 2003
L119 Which particular patterns are you referring to? Competition? Resource partitioning?
L134 How big were your grids? What was the total number of baits offered. One bait per point means 1 bait type, or one of each bait types?
L143-145 How many vials were used? How were they placed? How much propylene glycol was used per vial?
L147 Why are some ants used from some baits and not the others? Can fatty acid content be changed with food uptake? If so, how will bait consumption change your NLFA signature. Why aren’t NLFA at both sites sampled from the colonies, and how might that affect your results?
L151 You at least need to mention what solvent was used for your extractions, if nothing else
L155 Preservation of ants in 70% EtOH can alter carbon content. This needs to be addressed.
L194 What was PAST used for?
L262 If higher d’ value refers to the resource d’, then Feces has the highest d’ value in Brazil, higher than Large prey, and yet groups together with small prey, not separated as large prey in Figure 1. Perhaps providing more detail on which data was used to produce these clusters in the methods would help explain this clustering. In methods you say proportion of occurrence was used for Bray Curtis Analysis, but it’s unclear are you referring to the species level occurrence, or overall abundance of ants at baits
L423 Fluidity of what?
L425 If this fatty acid can be synthesized, why would ants store it throughout the year, and not just synthesize it in the fall?
L430 Here would be useful to see if this same NLFA was related to dead arthropod prey in the temperate zone as well. If not, then you can’t be using this paragraph L430-439 as an explanation.
L571 This is becoming repetitive, you already discussed distinct position of Wasmannia.
L594 How do you interpret high 15N then?

Overall I think the discussion would benefit from shortening, maybe even restructuring.


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: CONTRASTING GENE FLOW AT DIFFERENT SPATIAL SCALES REVEALED BY GENOTYPING-BY-SEQUENCING IN ISOCLADUS ARMATUS, A MASSIVELY COLOUR POLYMORPHIC NEW ZEALAND MARINE ISOPOD
Review round: 1
Reviewer: 1

Output:
Basic reporting: Refer to General Comments
Experimental design: Refer to General Comments
Validity of the findings: Refer to General Comments
Additional comments: The authors use a reduced representation genomic approach to investigate the hypothesis that colour polymorphism within populations of the isopod I. armatus is maintained by the action of divergent selection coupled with gene flow between populations. The authors are successful in validating the use of GBS markers to infer populations structure within and between Southern and Northern Island populations in New Zealand and they use these data to compare coalescent models differing in the direction of migration across regional and coastal spatial scales. The authors also demonstrate that few outlier loci identified as putatively under selection appear to be associated with distinct colour morphs. The mechanisms maintaining color polymorphisms in populations are certainly important evolutionary questions and I. armatus appears to be a useful model for testing such hypotheses. While individual genomic analyses seem to be well done and appropriate, I am not convinced that the hypothesis of interest can be explicitly tested from the data and analyses provided. There are several factors that weaken the study and the conclusions that can be drawn about the nature of selection and the impact of gene flow on CP. Nevertheless, the application genome-wide markers to infer population structure and make inferences about dispersal ecology in this system are useful and interesting and will be a valuable contribution if appropriate revisions are made.

Major Comments:

My main concern is that this study is framed in the context of understanding the evolutionary mechanisms maintaining colour polymorphism; however, the study design does not set up a test of this hypothesis, which would require both variation in the frequencies of colour morphs among populations and sampling populations with and without gene flow. No justification is provided on why selection is expected to act differently among populations in this system and it is not evident whether distinct colour morphs segregate between populations or habitats within populations. Instead, the discussion of the empirical evidence suggesting that selection may be operating on CP in I. armatus seems post hoc (L457). Furthermore, the effect of gene flow between populations and the processes occurring within populations that may contribute to the maintenance of CP cannot be detangled with the data at hand. More broadly, the mechanism by which directional selection and gene flow may act together to maintain CP within and between population is not clearly explained in the Introduction. Explicit predictions of this hypothesis would be useful.

Overall, while the results generally support the conclusions made, they do not match the early focus on CP and the processes maintaining CP. This mismatch is further evident in the Discussion, where emphasis is placed on the broader context of interpreting population structure and barriers to dispersal, rather than the implications for the evolution of CP. With that being said, I would suggest that the aims of the study relating to CP need to be removed entirely or revised to explicitly make this aim secondary to the main investigation.

My second concern is that MIGRATE model comparisons of gene flow do not allow for m=0 as the authors indicate. Plots of the posterior distributions of the migration parameters estimated by MIGRATE (prior to model selection) should be provided in the supplementary materials at the very least. It seems essential that specified priors capture the posterior distributions for accurate estimates of migration and therefore model support (L274). I would also suggest to draw direct comparisons of estimated m (the proportion of migrants per generation) between population pairs, rather than Nm, to avoid uncertainty in effective population size estimates.

The authors should also keep in mind that MIGRATE involves the assumption of migration-drift equilibrium such that all shared alleles between two populations are due to gene flow (refer to Kuhner 2009 TREE 24.2:86-93). Because your data includes populations distributed across small spatial scales that may have split only very recently (<4Ne generations), it is likely that some variants are shared by descent, rather than migration. Violations of these assumptions may therefore inflate estimates of gene flow, so it would be useful to touch on these caveats in your discussion. Consideration of demographic processes leading to population structure (i.e., historical isolation, rather than contemporary barriers to gene flow) should be given and these caveats should be discussed.

Additional Comments:

L40-41. Statement seems too general, as there are many examples of marine species with low capacities for dispersal.

L43-55. Discussion and references on the application of genomics in marine systems seem dated.

Figure 1. It would be useful to arrange images to allow direct comparison of colour morphs (i.e., striped morphs next to each other). Colour morph of (h) is not indicated in figure legend.

L82-85: Given the apparent continuous distribution of colour variation within populations, CP is likely to have a polygenic basis, and such caveats should be addressed.

L164: Unclear whether ‘call rate’ refers to mapping quality or ‘missingness’ across individuals.

L204: Some justification for including COANCESTRY analyses would be useful.

L227: Unclear which SNP dataset was used in the PCA analysis, and whether missing genotypes were removed following SNP filtering.

L356-358: Unclear how the strength of associations of two SNPs with striped colour morph was determined. Small sample sizes of the striped morph in particular may inflate false positive associations.

Figure 6 is missing. Based on the text alone it is unclear whether the PCA of selected SNPs was conducted for colour morphs across all populations and if the clustering of morphs is consistent when all samples from populations are considered.

L368: Unclear why emphasis on small marine species is relevant here.

Table 5. It seems unusual that more than 70% of the SNPs analysed in neutrality tests (3,892/5,236) are FST outliers among populations. Is this the total number of SNPs under selection in both FDIST and BAYESCAN analyses combined?

Table S1: Unclear what the values refer to. Locus ID? Table should include a legend.

L450-452: The interpretation that CP is maintained among species through adaptive processes entirely, seems speculative. Justification is required to explain why the maintenance of CP among species solely through demographic processes does not apply in this system - namely ancestral polymorphism, drift, migration in the absence of divergent selection.


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: CONTRASTING GENE FLOW AT DIFFERENT SPATIAL SCALES REVEALED BY GENOTYPING-BY-SEQUENCING IN ISOCLADUS ARMATUS, A MASSIVELY COLOUR POLYMORPHIC NEW ZEALAND MARINE ISOPOD
Review round: 1
Reviewer: 2

Output:
Basic reporting: This is a very clear and succinct paper addressing a preliminary study of population structure in a New Zealand marine isopod using population genomic techniques. It is an interesting topic, especially given the extreme colour polymorphism in the species, the methodological approach is appropriate, the writing is very clear and logical, and most of the conclusions are appropriate and justified.

The abstract is clear and succinct. The Introduction covers all the basic required background elements of marine population genetics, isopods, population genomics, and the genetics of colouration, and introduces the aims in a succinct manner. The Results are sufficiently presented and illustrated through tables and figures. The Discussion is appropriate and justified, apart from the points mentioned above. The referencing is quite comprehensive for a preliminary study.
Experimental design: The methods all appear appropriate and are well described.
Validity of the findings: My only criticism of this manuscript is that a reasonably large section of the discussion is spent on potential support in this data for a north-south genetic division, which has been seen in some other marine species in this region. My take on it is that, given the preliminary sampling analysed here, although the north-south division is relevant, this data set cannot yet really add anything to this debate. Thus this discussion should be reduced to a recognition of this existing pattern, and how it could best be tested in the future in this species. Instead, I think the authors should emphasise the obvious population strength of this preliminary data set, which is that their sampling at two different geographic scales has enabled them to already determine two important aspects of this species’ population structure: - a scale below which population differentiation appears to not occur (8km), and a scale at which population structure clearly does occur (North v South I.). This is exactly what is required from a preliminary study of this nature.

The authors also appropriately make two other preliminary conclusions from the data. That is, that the methodological approach provides appropriate data on genetic diversity for undertaking population structure analyses, and that, significantly, there is already some preliminary evidence that some of the colour polymorphism may be linked to simple genetic variation.

The claim that this is the first population genomic study on a NZ marine organism may not be justified (e.g., Villacorta-Rath et al, 2016 – see below), so I think it would be more appropriate to simply say it is one of the first studies.

Some detailed comments follow:

Line 26: - “ …one of  the first …”

37: - … remove most variation…

56: - not the first genomic study (see e.g., Villacorta-Rath et al 2016 below) – perhaps the first reported GBS study (depending on the definition of GBS). Probably safer to simply say “…one of …”
[Villacorta-Rath C, Ilyushkina I, Strugnell JM, et al. (2016) Outlier SNPs enable food traceability of the southern rock lobster, Jasus edwardsii. Marine Biology 163.]

69: - “…NZ marine Isopoda…”

Fig 2:
A – should be a table? Or actually incorporated into the fig.?
B – the choice of colour of landmass (light blue) may perhaps not be the best contrast for publishing

150: - “…were processed…”
155: - “…a cheaper version…”
176-200: - a pop structure analysis on those loci potentially under selection may also be interesting to see at a later stage

Table 1 could go into appendices?

Table S1 requires additional explanatory text as fig legend (in my copy)

I don’t see fig 6 – it should be either included or reference to it removed

366: - I don’t think this is true – see above for 1 e.g.,

**397-441: - although interesting, and a good reflection of the current marine phylogeographic literature in NZ, given the sampling, a lot of this discussion is a bit speculative & somewhat irrelevant– can only say that sig. differentiation occurs at a scale >8km

Better to focus on the strength of analysis of different scales, & potential correlation of some markers with morphology

Good conclusions
Additional comments: This is an excellent preliminary paper and I look forward to seeing progress on this study.


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: CONTRASTING GENE FLOW AT DIFFERENT SPATIAL SCALES REVEALED BY GENOTYPING-BY-SEQUENCING IN ISOCLADUS ARMATUS, A MASSIVELY COLOUR POLYMORPHIC NEW ZEALAND MARINE ISOPOD
Review round: 2
Reviewer: 1

Output:
Basic reporting: Refer to general comments to the author.
Experimental design: Refer to general comments to the author.
Validity of the findings: Refer to general comments to the author.
Additional comments: I have re-read the revised manuscript carefully and I feel that the authors have addressed my comments and the suggestions from the other reviewer appropriately. I would recommend the revised paper for publication.

Overall, the revised Introduction and study aims (i.e., shifting the primary focus away from CP) are much better suited to the results and the conclusions of this study. The authors’ scaled back interpretation of the results relating to selection and the limited inferences that can be made about the maintenance of CP seem more appropriate. The assumptions and caveats regarding Migrate analyses are well written. I also appreciate the additions of supplementary figures illustrating the posterior distributions of the estimated migration parameters. I have a few suggestions for minor clarifications below.

183-184: Unclear filtering criteria regarding linked loci. Clarification would be useful.

276: What is the generation time assumed for this species?

387: putatively non-neutral

407: More explicit statement of this hypothesis would be useful in the Introduction. It is unclear whether you predicted to observe genetic structure at small spatial scales in this species as you argue for both strong swimming ability and previous studies indicating substructure across microhabitats.

474: Seems unlikely, given that such patterns are reported among northern and southern populations of other species in this region. I agree that sequencing COI will be useful prior to future analyses of CP in this system.

488: one component of CP


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: GLOBAL MAPPING OF POTENTIAL NATURAL VEGETATION: AN ASSESSMENT OF MACHINE LEARNING ALGORITHMS FOR ESTIMATING LAND POTENTIAL
Review round: 1
Reviewer: 1

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: This paper is well structured and written. It compares four machine learning methods for potential natural vegetation (PNV) mapping from climate and environmental covariates. The results show that the random forest performs the best, which is coherent to many other findings solving classification/regression issues. I have a minor comment on this paper.

Many of MODIS FPAR is from the vegetation that has been affected by human activity. In the training stage, the author applied the WDPA and IFL mask to select samples with minimum affection by human activity. These two masks make the training pool data spatially unevenly distributed. Please clarify whether random sampling or stratified sampling is applied and discuss its possible effect on the results.


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: GLOBAL MAPPING OF POTENTIAL NATURAL VEGETATION: AN ASSESSMENT OF MACHINE LEARNING ALGORITHMS FOR ESTIMATING LAND POTENTIAL
Review round: 1
Reviewer: 2

Output:
Basic reporting: This manuscript is aimed to produce PNV maps that are both more detailed, richer in information, based on multiple machine learning algorithms.
The writing is clear enough, however the manuscript contains a number of spelling and grammatical errors which should be carefully revised before acceptance.
The literature is suitable for the purpose of the article.
Experimental design: no comments
Validity of the findings: The data are robust and results compatible with conclusions.
It is necessary to present evaluation of TPR outliers in the Table 2. (e.g., Carpinus orientalis and Cupressus sempervirens).
In the revision round, it would be interesting to compare the performances of multiple MLA.
Additional comments: 1.	As the title of this manuscript listed “Global Mapping of Potential Natural Vegetation: An Assessment of Machine Learning Algorithms for Estimating Land Potential”. Content of PNV and FAPAR is too much in the manuscript. Authors should focus on the effect on wind erosion potential by land use/cover changes and land management practices.
2.	The text is extensive and repetitive in many parts. Thus, I recommend rewrite abstract and introduction. The conclusions can be improved.
3.	There are some sentences which are difficult to understand, for instance:
        Page 4/lines 105-106: For efforts aimed at land restoration ....
        Page 9/lines 239-240: We use about 3× more training points ....
        Page 12/lines 344-346: TPR values range from 0 to 1 where 1 ....
        Page 16/lines 394- : Results of the spatial Cross-Validation, as implemented ....
4.	The figures should be renumbered accordingly such that they are introduced in the correct sequence (e.g., Fig 1). You did not mention Fig 1a in the manuscript.
5.	The time stamps in Figure 9 are hard to read, as are the lines in Figure 10, which makes them difficult to interpret. There seems to be no explanation in the Figure legend or any values which describe the distribution of the tree species, it may be helpful to put these directly in the Figure.
6.	The reference citation in the title of Table 2 is inappropriate. I recommend deleting the citation and placing the correlated content information in the text. The Species name of forest tree taxa should be placed in italic type.
7.	The spatial resolution of Input data (environmental covariates) should be illustrated in detail.
8.	Line 287 The resampling methods of nearest neighbor interpolation, bilinear interpolation, and cubic convolution interpolation were commonly used. In this study, which one were used?
9.	The model inputs seem to be complicated. It would be better to have a schematic picture that shows the model framework.
10.	The abbreviation of Scaled Shannon Entropy Index has two forms (EIs, SSEI, NDVI and some other technical terms) should be uniformed, and the corresponding full name should be given. Work on text clarification and formatting, improve figures, list of the abbreviations would be useful in this case to easily understand the text.
11.	The quantitative comparison of results of modeling potential distribution of tree species in Europe should be illustrated, not only the visual comparison.
12.	The calculating equations of RMSE and ME should be listed as standard equations with number (Page 13/line 366). The variables in the equations of them are not explained.
13.	More discussions on the ecological gradients should be added to the manuscript.
14.	The detection and assessment of PNV is critical for the prevention of environmental deterioration especially in arid and semi-arid areas. Hence, I propose to consider the special region.
15.	The altitude, topography and soil types might have a certain impact on the PNV. Due to the lack of information it is not clear the need of pooling all data together. I am wondering if by comparing different climate (soil/topographical) regions and analyze the response of the methodology under these scenarios would not produce better results. In any case, this discussion was missing and need to be clarified.
16.	The challenges and limitation in mapping PNV using MLA should be further highlighted in the discussion.
17.	Line 416 “Correlation analysis (predicted distribution maps) indicates that…” is not clear enough. Which fig (did you mean fig. 6)? There should be more details here.
18.	In general, the machine learning algorithm with more parameters or hyper-parameters could lead to more complicated training, though it has better accuracy. A good algorithm should have good accuracy and meanwhile, include less trained parameters. It looks that RF has more complicated hyper-parameters. More discussions on this point should be added to the paper.


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: GLOBAL MAPPING OF POTENTIAL NATURAL VEGETATION: AN ASSESSMENT OF MACHINE LEARNING ALGORITHMS FOR ESTIMATING LAND POTENTIAL
Review round: 1
Reviewer: 3

Output:
Basic reporting: This paper is well written and fits into the scope of this journal. This study contributes to the current knowledge of natural vegetation mapping using data-driven approaches. The methodology presented in this study would help other researchers to replicate the methods and apply to other parts of the world, provided all the data used in this study are available.
Experimental design: Modeling of natural vegetation across the globe using statistical and machine learning models is very useful for biodiversity management, and help quantify the effect of climate change and human activities on existing vegetation. Empirical/data-driven models can serve as surrogates to computationally intensive physical/numerical vegetation models. The authors did a commendable job in collecting the huge amount of data and developing models that bridge the gap between existing models and present knowledge of vegetation mapping.
Validity of the findings: Conclusions are well presented and answer the research questions.
Additional comments: 1. Line 23: PNV is already spelled out in line 20, so just say PNV here.
2. Could you please elaborate the 'time' label on x-axis?
3. Fig. 12: Bottom figure: It should be predicted FAPAR.
4. Please include a section on assumptions that are considered in this study or as a section describing limitations of the modeling framework. I would keep all the assumptions in one place to get a complete picture of what data are available and what are the limitations.
5. Fig. 14: Please elaborate 'To convert to percent divide by 253'.
6. Did you run your models on GPU, if yes give the specifications.
7. How long does it take to run each model (random forest, neural network etc.)? Please provide a comparison of computation time, performance, parameter sensitivity etc. maybe in the form of table for better understanding.
8. Could you please provide a comparison of the best-predicting model results to ground-truth observations?
9. What are the percentage of relevance of the most important predictors like precipitation, temperatures etc.? Can you calculate those from connection weights of the neural network?
10. It would be nice to refer some of the recent machine learning papers in related field.
For example:
Deo, R.C. and Şahin, M., 2015. Application of the extreme learning machine algorithm for the prediction of monthly Effective Drought Index in eastern Australia. Atmospheric Research, 153, pp.512-525.
Sahoo, S., T. A. Russo, J. Elliott, and I. Foster (2017), Machine learning algorithms for modeling groundwater level changes in agricultural regions of the U.S.,Water Resour. Res.,53, 3878–3895, doi:10.1002/2016WR019933.
Okujeni, A., van der Linden, S. and Hostert, P., 2015. Extending the vegetation–impervious–soil model using simulated EnMAP data and machine learning. Remote Sensing of Environment, 158, pp.69-80.
Li, X., Chen, W., Cheng, X. and Wang, L., 2016. A comparison of machine learning algorithms for mapping of complex surface-mined and agricultural landscapes using ZiYuan-3 stereo satellite imagery. Remote sensing, 8(6), p.514.


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: GLOBAL MAPPING OF POTENTIAL NATURAL VEGETATION: AN ASSESSMENT OF MACHINE LEARNING ALGORITHMS FOR ESTIMATING LAND POTENTIAL
Review round: 1
Reviewer: 4

Output:
Basic reporting: The work presents a comprehensive study of the effectiveness of different machine learning approaches (in particular, Artificial Neural Networks, Random Forest, Generalized Boosted Regression and K-NN) applied to the global mapping of Potential Natural Vegetation (PNV). In general terms, it is an interesting contribution. It is well structured, follows a clear methodology and provides a wide experimentation. The writing is good, which is accompanied by visual content that facilitates its understanding. The paper meets all the requirements to be accepted. However, there are minor modifications that may greatly improve the dissemination of the performed research
Experimental design: Although the experimentation is appropriate, the paper would gain in interest if it would provide a more in-depth discussion about the motivation that led to select the implemented algorithms, as well as their hyphotetized benefits/drawbacks when applied to PNV mapping.
Validity of the findings: The extensive and methodical experimentation proves the effectiveness of the selected methods. However, the paper would gain in clarity if the achieved results were correlated with the characteristics of the algorithms (from the ML and pattern recognition point of view).
On the other hand, I suggest to enhance the criteria considered for estimating the best TPR, since the ROC curve covers the spectrum of all possible values based on calibration, and a simple average may mislead the results interpretation. Maybe the best Youden index could fit with the experimental purposes.
Additional comments: The paper provides an interesting contribution, which a well-described research methodology and an extensive experimentation. Hence it meets all the requirements to be accepted


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: EYE MOVEMENT CONTROL DURING VISUAL PURSUIT IN PARKINSON’S DISEASE
Review round: 1
Reviewer: 1

Output:
Basic reporting: Grammatically sound and overall well-written.
Referencing is adequate and appropriate
The article is well-structured, and whilst the Figures are of reasonable standard, it would have been helpful to include some raw traces of the fixation and pursuit data, to better determine the 'saccades' that the authors analysed. Figure 7 is missing the units on the y axis.
There is some repetition in the discussion (e.g. lines 391-399).
The article is self-contained.
Experimental design: The rationale for the methodology used could be better described. For instance, I am not clear why the paradigm combined a fixation period followed by a moving target arising from the periphery. What is the added benefit of this design compared to a 'fixation' paradigm, followed by a second 'pursuit' paradigm? Specifically, I suspect that the arrival of a pursuit target from the periphery would have added a distractor that may interfere with fixation. If such a 'distractor' was used to introduce greater potential for saccade disinhibition, then should be explicitly mentioned.

The authors should also better define the rationale for using the dichoptic and stereoscopic displays. It seems perhaps more relevant to use this for the pursuit paradigm, so the benefit of using it for the fixation section should also be explained.

I am not convinced that the current methodology was indeed assessing any convergence, so this needs to be explained.
Validity of the findings: The key findings are:
1. Reduced pursuit gain in the PD group
2. Increased number of saccades during pursuit in the PD group -I am however not clear what these 'saccades' actually are. Their frequency would suggest that they may be square wave jerks, and thus not intrusive or affecting fixation. There is no description of the plane of the saccades, their peak velocity, or amplitude.
3. Increased inter-ocular distance (divergence) during pursuit in the PD group, that was not affected by dichoptic viewing, and was not correlated to disease severity. Did patients report any diplopia during pursuit (there is a case report of 'Motion Diplopia' in Clinical Neurology & Neurosurgery by Kaski et al. the context of ophthalmoplegia that may be of relevance for the discussion).
4. That the increase in saccades during pursuit is un-related to any phase-lag. Again, it is imperative to understand what these saccades actually look like - are they square waves or intrusive (i.e. larger amplitude) saccades?
Additional comments: Overall, the results are of interest, but the methodology needs a more robust rationale. As it currently reads, it is not clear why the paradigms were chosen, and it seems that he authors have perhaps introduced quite a few different variables here, all in the same paradigm, rendering interpretation of the findings quite challenging.


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: EYE MOVEMENT CONTROL DURING VISUAL PURSUIT IN PARKINSON’S DISEASE
Review round: 1
Reviewer: 2

Output:
Basic reporting: Well-written and logically organized.

I found the use of "involuntary" saccades in the title and abstract misleading.  I much prefer the more descriptive and accurate "saccades during pursuit" (or even something like "catch-up saccades") that is used throughout most of the manuscript.

The stated interest in "age" comes out of nowhere in the Introduction (3rd to last sentence).  It would be nice to tie that in somewhere earlier if possible.

Line 355: missing word.  "there was difference in saccade"

The data shared are not the raw data.  As I understand it, the full raw data are 30 6-second trials for 3 groups (PD, NC, YC).  The raw eye position data (e.g., Fig. 6) can and should be easily shared, preferably in a .mat Matlab format but even in Excel would suffice.

Fig 1 should be black and white in my opinion.  Color does not seem necessary.

Fig 2: Top row need a y-axis label, not just a unit ("degrees").  e.g., Horizontal position offset?  Also, would be useful to put a label for each column in the top row (YC, NC, PD).
Experimental design: Excellent motivation and research question.

Eyetracker calibration info should be included in the methods.  The calibration issue is the most important and troubling aspect of this manuscript.  Potential differences in eyetracker calibration between subject groups are not addressed until the very end of the manuscript.  Calibration would not affect fixation and pursuit equally as the authors claim because the physiological demands of each are different.  Pursuit is driven by retinal slip so 1-2 deg of visual angle of slip away from the pursuit target would elicit pursuit while fixation would largely be unaffected by 1-2 deg of movement within a fixation window, which is a typical fixation window size.  (The authors do not mention any restrictions or viewing windows for their task).

This phrasing initially made me think that the 10/20 trials were *practice* trials, which they are not.  Consider improving the language for clarity: "To familiarize observers with the task, we conducted a set of practice trials before the experimental trials. There were 10 trials in the binocular viewing condition and 20 trials in the dichoptic viewing condition. Each trial lasted approximately 6 seconds."

What exactly is steady state pursuit?  I see that a Heinen paper is referenced for the interval used (500-700 ms) but groups like Osborne and Lisberger labs tend to use some "initiation/open loop" interval from ~0-150 ms and steady state presumbly begins after that initiation period.  Why the large discrepancy?  Does this matter?

How exactly were saccades excluded?  Those trials were discarded or the data were interpolated?
Validity of the findings: Line 233: Sentence started "Even though..." could use a statistic or some quantification to support this claim.

Line ~266: Could you make a polar plot of the direction of PD saccades to demonstrate your point?
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: EYE MOVEMENT CONTROL DURING VISUAL PURSUIT IN PARKINSON’S DISEASE
Review round: 1
Reviewer: 3

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: See comments below.
Additional comments: The manuscripts studies eye movements in PD patients during pursuit. It shows that there are more saccades during pursuit in PD than in controls and that there is more disparity between the left eye and the right eye in PD than in controls. These results are interesting and worth publishing. However, with the current analyses is not possible to discard the possibility that some of the results are not due to poorer quality recordings in the PD patients than in controls. A few additional analysis could help solidify this point.
Major comments:
-	The discussion about calibration is not correct. First calibration and noise are two different things. Calibration is related to accuracy, while noise relates to precision. You could have a perfect calibration with high noise or a terrible calibration with no noise. Second, the calibration, in the simplest case will have an offset component and a gain component. It is possible to calibration a proper offset from a wrong gain. Thus, there are many scenarios that could indeed produce some of the results found in the study. It is possible and even likely that calibration and/or noise are different or each eye. For, it could be possible that both eyes have a correct offset, so fixation looks ok, but gain is wrong on one eye only so as soon as the eye moves away from center disparity increases. Eyelink eye trackers use polynomial fits for calibration that are a bit more complicated to interpret but would be susceptible to same type of problems.
-	It would be helpful to show a main sequence of the saccades detected in the three populations both during fixation and during pursuit. A clean main sequence (peak velocity vs. amplitude) would be a strong indication that the saccades being detected are real and not just caused by noise.
-	It is unclear how many of the saccades analyzed are saccades that occur during pursuit initiation and how many are proper involuntary saccades during pursuit. Authors may want to analyze separately the saccades that occur during the first 0.5 s of pursuit and the ones occurring after, during steady state.
-	The dichoptic condition misses a key analysis. It should include a comparison of the eye that sees the target vs the eye that does not see the target. Instead of plotting eye position difference authors could plot eye to target difference. This would allow to distinguish between three possibilities. A) the eye that sees the target is pursuing well but the other eye is not. B) both eyes are pursuit poorly and independently. C) Data from one is worse not matter if it is the one seeing the target or not.

Minor:
•	Did the polarizing glasses affect the eye movement quality in any way? Did the cameras of the eye tracker saw the eye through the glasses?
•	Until what eccentricity did the target move during the pursuit? Also 22 degress?
•	Was there any point in randomizing the latency of the pursuit start? It will still be completely predictable when they have to start pursuit after seeing the target moving toward the fixation spot.
•	Figure 2: it would be clearer to show also a row with the actual average eye position together with the target position.
•	Figure 3: It would be helpful to remind the reader that the gains were calculated on the 500-700 ms window after pursuit onset. Otherwise it appears to contradict Figure 2.
•	Figure 4: what windows of time where used for this analysis? -1.5 to 0 and 0 to 1.5?


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: EYE MOVEMENT CONTROL DURING VISUAL PURSUIT IN PARKINSON’S DISEASE
Review round: 2
Reviewer: 1

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: The authors have addressed the reviewer remarks satisfactorily and I have no furtherr comments to add.


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: EYE MOVEMENT CONTROL DURING VISUAL PURSUIT IN PARKINSON’S DISEASE
Review round: 2
Reviewer: 2

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: Much improved.  All issues addressed.  Good work.


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: WHAT AFFECTS POWER TO ESTIMATE SPECIATION RATE SHIFTS?
Review round: 1
Reviewer: 1

Output:
Basic reporting: This manuscript is generally well organized and logically structured, the figures are high quality and very clear, and the manuscript generally fulfills basic reporting. I have only a few very minor concerns here:

1. The supplementary data archive is very thorough, and seems sufficient to recreate all of the major results. However, the code for simulating trees is relatively undocumented and difficult to interpret. You should provide more detail about the logic and details of this simulation in the code and manuscript (I will return to this point in the Experimental Design section). Additionally, a README file in the FigShare archive would help readers understand the workflow of the simulation and analysis, and would facilitate transparency and replication.

2. On line 29, you seem to attribute the "advent of phylogenetics" solely to Hennig 1965 (presumably you mean "phylogenetic inference", as the concept of phylogeny itself has much deeper historical roots). Certainly phylogenetic inference has a complicated origin, but if you are going to cite specific works then it would be reasonable to cite Edwards + Cavalli-Sforza 1963, Sokal + Sneath 1963, Camin + Sokal 1965, among others, as early examples of phylogenetic inference per se.

3. I disagree with your citation and interpretation of Hartmann, Wong, and Stadler (2010) on line 125. This misinterpretation underlies a more serious conceptual issue with the experimental design, so I will go into more detail on this concern in that section.

4. There are some grammatical and typographical errors; I am providing a details list below of the errors I identified:

- line 19: "For BiSSE, we assigned different character states for the lineages with different simulated speciation rates." This seems like a technical detail that does not need to be in the abstract.

- line 21: "... but had high Type II errors" -> "... but had high Type II error rates".

- line 22: "algorithms" -> "methods", just for consistency.

- line 22: "identified" should probably be "identify", to maintain the present tense when referring to the results

- line 23: "both" -> "all three"

- line 24: "performed" -> "perform", as per comment about line 22

- line 50: "models estimate" -> "methods estimate". "Models" allow us to compute probabilities, but do not themselves estimate parameters. "[statistical] methods" use probability calculations provided by models to estimate parameters.

- line 51: The use of "information" and the description of the types of "information" here are confusing. Clade age and branch lengths are not very distinct from each other. I would just say along the lines of "These estimates are based on divergence times(/branch lengths) and the topological distribution of species among clades", or something similar.

- line 54: What does "diversity" mean here? All lineages are elements of diversity. Are you referring to diversity-dependent models? Please clarify.

- line 73: "without a priori information on character states". It would be more accurate to say that the character-independent diversification model are agnostic about the mechanism of rate variation, not that they are agnostic about the character state. The source of rate variation need not be a character in the standard phylogenetic sense, but could be, for example, a unique historical event. Invasion of an island (an event) may lead to increased diversification rates; this is distinct from the idea that living on islands (a character state) increases diversification rates.

- line 80: "estimations" -> "estimates", plus comments about BAMM, above.

- line 86: "were" -> "are"

- line 92: "the of estimates" -> "the estimates"

- line 93: "the BiSSE" -> "BiSSE" or "the BiSSE method"

- line 96: "estimation" -> "estimates"

- line 124: "simulation of branching process conditioned on number" -> "simulation of branching processes conditioned on the number"

- line 145: ";;" -> ";" within the parentheses.

- line 150: "Bage" -> "B_age"

- line 164: "for a sample trees" -> "for a sample of trees"? Also, why just a sample of trees? MCMC is not especially costly: you should do this for each analysis.

- line 176: I assume "pure birth-death process" -> "birth-death process"?

- line 231: "(Type II error, red curves in Figure 1)" Should this refer to Figure 2?

- line 284: "readers" -> "researchers"?
Experimental design: The goal of this research is to understand the statistical behavior of some of the most popular methods in the study of phylogenetic/macroevolutionary lineage diversification. This is very well motivated: the lineage diversification field is currently in a bit of disarray, and a thorough presentation of how these methods behave would be extremely timely and valuable to the community! Unfortunately, the execution of the simulation study has serious flaws, which I detail below.

In order to receive my recommendation for publication, you should develop a reasonable strategy for simulating data that is as close to the generating models as possible, so that the impact of model misspecification on power and parameter estimates is minimal. The BAMM and MEDUSA analyses should also be performed to a higher standard (see the specific sections below regarding my concerns).

1. The data are simulated in a very ad-hoc way.

You note that "simulation of branching process [sic] conditioned on number of tips can lead to bias in the diversification rate (Hartmann, Wong, and Stadler 2010)". This is a misinterpretation of the Hartmann paper: the issue they identify is with an incorrect procedure for forward simulating trees conditional on the number of species under a birth-death process (it is incorrect to terminate the simulation as soon as there are exactly #n species in the tree). Their point is that, when you simulate data incorrectly, parameter estimates based on those simulations will be biased. They show that it is straightforward to 1) correctly simulate trees conditional on the number of species, and 2) generate unbiased parameter estimates on the resulting trees. This might seem irrelevant, but the issue that Hartmann, Wong and Stadler identify is _directly_ applicable to your simulations: ad hoc simulation procedures result in biased parameter estimates.

One appealing property of model-based inference methods is that, in theory, as the amount of data increases to infinity, parameter estimates converge to the true value (for well-behaved, so-called "consistent" statistical methods). However, this is only true if the inference model and the generating model are the same: obviously, if the inference model is wrong, then parameter estimates can never be perfect. For example, if you simulate trees conditional on the number of species, and estimate parameters conditional on the age of the tree, parameter estimates will be compromised. This consideration implies that ANY discrepancy between the generating and inference models can compromise statistical performance. This is concerning because your simulation procedure is not a "generating model" for any of the inference models that you use. It is therefore very difficult to understand whether the issues you ultimately identify are properties of the methods (statistical behavior) or are just an artifact of your simulation procedure.

In short, I do not think the experimental design you have chosen is justifiable, and it obscures the interpretations of your results. In general, if you want to understand the statistical performance of a method, you need to simulate data under a model that resembles the inference model as much as possible. Otherwise, if the method performs poorly, we do not know whether it's because of a property of the method or because of the simulation procedure! This is effectively an uncontrolled experiment. One solution to this problem would be to simulate data under the models assumed by each method. I know this is an impossibly tall order: MEDUSA in fact does not describe such a model, and the model assumed by BAMM has become increasingly ambiguous and may be impossible to simulate under.

Another solution would be to focus on "empirical performance" rather than "statistical performance". An alternative approach to simulation studies is to try to understand how biologically realistic violations of model assumptions compromise parameter estimates. In this case, we may simulate data under some well-motivated but non-generating model, and check parameter estimates under the inference model to see how accurate they are. This will give us some idea about how reliable the parameter estimates are given some biologically realistic part of parameter space. This, however, requires some sense of "biologically realism", which is difficult to quantify, and is quite different from the approach of the current manuscript!

(As a technical asside, I will note that TESS does not use forward simulation (line 121), nor does TreeSim use backward simulation when conditioning on age (line 133). These details aren't really critical to the present work anyway, so I think they can be safely omitted.)

2. Your exploration of parameter space further obscures behavior.

Specifically, because you simulate conditional on a small number of tree ages (25 and 15), tree size (number of taxa) is conflated with rate shift size. The size of the tree is proportional to the amount of information available to estimate parameters, so is the observation that power increases as rate shift size increases an artifact of tree size?

It would be better to adjust the tree age for a particular combination of simulation parameters so that the expected number of species hits some target value; you may iterate over target values to achieve differences in tree size. So that tree size and rate shift size are not correlated, it is critical that the expected number of species is for the entire simulation procedure, not just the "basetree". This can be achieved by Monte Carlo simulation: for a given tree age and set of simulation parameters, simulate many trees and compute their average age; repeat until you find an age that provides the target number of species. In this way you could simulate small trees with large rate shifts by decreasing the age of the tree.

As far as the combinations of parameters you choose to simulate, e.g., the ratio of basetree speciation rate and subtree speciation rate: how did you choose these values and why? For example, you use only a single---relatively low---value of the extinction rate; we know these methods are sensitive to the (relative) extinction rate (May and Moore 2015), so I consider this a serious limitation. Your lambda_1/lambda_0 ratios are quite finely divided: this isn't a bad thing by itself, but is probably very inefficient. If you want to explore more extinction rates, then using ratios at 0.5 intervals should be sufficient. I would also like to see ratios greater than 2.5. Especially if you are demonstrating that the methods have low power for small trees, it would be nice to know how large the rate shifts have to be to get good power for these trees!

3. The analysis of your simulated data is inadequate.

One major concern here is that you are using a very loose definition of a "true positive"; in particular, on line 150, you note that you compute "the proportion of trees in which a significant rate shift was detected." Is simply detecting a rate shift sufficient for MEDUSA and BAMM? Especially for methods we know can have high false positive rates, it seems like we should be checking whether or not the inferred location of the rate shift is correct. A "true positive" should be required to identify not just the number but the location of rate shifts!

3.1 BAMM (lines 160-172).

In general there needs to be more detail provided on these BAMM analyses. What priors did you use and why? It looks as if you used "default" exponential(1) priors on the speciation and extinction rates, and on the expected number of events. (These details need to be in the main text, as some of your readership may not be able to determine this from your supplementary files.) Is the behavior of BAMM sensitive to these priors? If so, then your current results would be uninformative. If you really want to understand how BAMM behaves in general, you need to give some thought to prior sensitivity (as you would with any Bayesian method). The developers of BAMM do not advocate using these default values, and provide a function (setBAMMpriors in the BAMMtools package) for generating not-unreasonable priors.

What does it mean for BAMM to "report >0 rate shifts" (line 171)? I can see from your supplementary material that you used the number of shifts with the highest posterior probability (the maximum a posteriori estimator, or MAP). Why? This is an especially bad choice, since a) the MAP estimate masks prior sensitivity and posterior uncertainty, and b) your prior expected number of rate shifts is 1. What happens if you use the posterior mean number of rate shifts? Again, it seems important to determine whether the _location_ of the rate shift was correctly identified!

It seems from your supplementary files that your BAMM analyses were only performed for 25 out of 100 simulated trees per combination of parameter settings. Is this a mistake in the supplementary data? If not, this needs to be explicit in the manuscript (though it would be preferable to do all 100 analyses).

3.2 MEDUSA (lines 173-178).

On line 175, you say: "We specified the model of tree evolution to be a Yule process as the model did not converge for mixed or pure birth-death process". This is quite troubling. First, how pervasive was this phenomenon? Did you try different initial conditions (the init argument)? I tried MEDUSA on a few (100) of your trees and it seemed to work fine! If the method doesn't work for computational reasons, it is a bit unfair to constrain the method in some way if you are really interested in the statistical behavior. I would recommend getting the method to work; if you cannot do so, then do not present these results!
Validity of the findings: Given the concerns outlined above, it is difficult to make much of the research findings. The interpretations of the results, taken at face value, are adequate. However, the advice given for methods developers and users of these methods is unclear, ambiguous, and/or unsafe---major revisions to the advice provided in the discussion section are required before I would recommend acceptance of this manuscript.

1. Results

For the reasons described above regarding the simulation design, it is difficult to make much of the results. All four variables (speciation rate symmetry, relative subtree age, overall tree age, and number of tips) are conflated because of the design of the simulation experiment, so we're effectively unable to understand factors that impact power. The simulated data depart to an unknown degree from each of the inference models, so it is difficult to interpret the biases in parameter estimates. Accommodating my advice about the experiment design, above, would alleviate both of these issues.

Also, from Figure 5 it looks like you are only reporting BAMM results for lambda_1/lambda_0 >= 1.5, whereas you are reporting results for this ratio of 1.1 for the other BiSSE. Is this intentional?

2. The advice given to method developers and users is unsound, or otherwise requires major clarification.

You say starting line 271: "the effects of tip number (both subtree and overall tree), and associated parameters such as relative subtree age, may be the most serious and universal issues for modelling approaches, and development of future methods should focus attention on rectifying these." It's not clear to me what you mean, here. Tip number and relative subtree age are properties of the data, not the method. I don't agree that these are issues of modelling approaches; rather, I see them as limitations on methods imposed by the data! Could you clarify how you expect method developers to use your results?

On lines 279-281, you say: "Users should be extremely cautious when using BiSSE, BAMM or MEDUSA on small phylogenies and should avoid using small, incomplete phylogenies to test hypotheses of rate shifts." Given that your results seem to suggest these methods have low power for small trees, I disagree with this sentiment; rather, I think users should be mindful about how they interpret the outcomes of hypothesis tests. Failing to reject a null hypothesis is not the same thing as confirming the null hypothesis! In this sense there is no "danger" of using a small tree: failing to reject rate constancy does not mean that there is no rate variation! Likewise, parameter estimates for small trees should have wide confidence/credible intervals and be interpreted accordingly. Could you clarify why you think we should be especially cautious? Excess caution does not seem to be supported by your results.

On line 281, you say: "When testing hypotheses of change in speciation rates, we recommend that users explore results from multiple datasets, such that the relative age of the clade of interest with respect to the entire tree varies." Unless I am misunderstanding your intentions, I find this advise dubious and impractical (many clades will not have multiple "datasets", depending on your definition of a dataset). Could you provide more detail on what you are suggesting? If you think that the power of the method depends strongly on the relative age of the subtree and are suggesting that users try datasets with different relative ages, this advise seems dangerously close to "fishing for significance".

Starting line 283, you say: "In analyses of trait-dependent diversification rates, we also encourage readers to report results from traditional sister-group species richness comparisons such as the richness Yule test (Paradis, 2012), and recently developed non-parametric tests such as FiSSE (Rabosky & Goldberg, 2017)." Again, I find this advice of questionable statistical merit. What is the purpose for doing this? One interpretation is that you are suggesting a simple sensitivity analysis: since all these methods differ slightly in the assumptions they make, then if all the methods agree, the result is "robust" to different assumptions---in principle, this would be a fine recommendation. The danger of this approach is an inflated sense of confidence. Certainly the results of multiple methods applied to the same dataset will be correlated with each other? I imagine that for your own simulations, when BiSEE correctly identified a rate shift, that both MEDUSA and BAMM were more likely to also identify that rate shift? The resulting "pseudo-consilience" runs the risk of providing the user with a false sense of the actual support for the hypothesis. If you are going to give this advice, you need to clarify what you are suggesting and give some thought to how multiple statistical analyses of the same data should be interpreted.
Additional comments: no comment


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: WHAT AFFECTS POWER TO ESTIMATE SPECIATION RATE SHIFTS?
Review round: 2
Reviewer: 1

Output:
Basic reporting: I have a few concerns about reporting:

1. Figures 3 and 4 are hard to interpret.

The goal of figure 3 (in my interpretation) is to show that these methods generate biased estimates of the relative rate of speciation between the subtree/basetree. However, the fact that the "target" ratio changes for each row makes it difficult to see patterns in the bias as a function of the relevant parameters. Rather than simply showing the median estimate of the rates in each cell, it may be more clear to show the mean (or median) percentage error in each cell (the average difference between the estimate and the true value, divided by the true value). The advantage of this measure is that it has the same "target" value, 0%, regardless of the ratio. Also, I think the term "expected speciation asymmetry" is not quite correct: this is really the true value, and not the expected value of an estimator or a random variable (which is what "expected" immediately makes me think of).

Figure 4 is very difficult for me to wrap my head around. I do not think that barplots are the right way to display this information. I would use Fig. 1 from Davis, Midford, and Maddison (2013), which shows power as a function of the tip-ratio, as a template here.

2. Miscellaneous

There are also some typographical errors and other minor issues related to reporting. Here is a (non-exhaustive) list of minor issues:

Abstract: the authors mention that lineage-diversification methods allow "researchers to correlate diversification rate shifts with causal ecological factors", but in the introduction they describe the various hypotheses that these methods are intended to address (traits, key innovations, biogeography, climate, etc.). To describe the latter set as "ecological factors" is a bit too narrow: I would recommend ammending the abstract to reflect that these methods are useful for more than just testing ecological hypotheses.

line 41: "'key innovations')(e.g." -> these two parentheticals should be combined.

line 44: e.g.Jansson -> e.g. Jansson (missing space)

line 58: "For long" is a fairly unnatural way to begin a paragraph. I might replace this with "Historically," or some equivalent conjunction.

line 67: "likelihood model" should just be "model", or "stochastic model" or "birth--death--transition model". Stochastic models provide ways of computing probability functions that can be used as likelihood functions.

line 68: "( Maddison" -> "(Maddison" (extra space)

lines 69-72: The language used to describe likelihood-based inference and model comparison is a bit murky, and should be clarified. The likelihood score is proportional to the probability of the data given a set of parameters. Maximum likelihood methods find the values of the parameters that maximize the likelihood score. The values of the parameters that maximize the likelihood are the maximum-likelihood estimates of the parameters. The maximum likelihood score can be used to compare competing models using, for example, the likelihood ratio test or AIC. (To be more specific: "likelihood scores" are not "estimated simultaneously for" parameters.)

line 96: "Markov Chain Monte Carlo" -> "Markov chain Monte Carlo" (chain is not capitalized)

line 106: "BiSSE has been shown to be affected..." This phrase is a bit vague. I would say that "The ability of the BiSSE method to detect state-specific diversification rates has been shown to depend on tree size and tip-ratio bias: the method seems to behave well with large trees and low tip-ratio biases" (or perhaps something more concise).

line 160: "detecte" -> "detect"

line 172: "mu_1 )" -> "mu_1)" (extra space)

line 223: "Sage" -> "age" should be subscripted.

line 348-352: "lineage" is used in an unusual way. Typically, "lineage" refers to a branch in a birth--death model, but here it is being used to describe the branches associated with a particular character state. These sentences should refer to the number of lineages in each state.

line 375: "When testing hypotheses of character-dependent diversification, users typically have information through ancestral state reconstructions on the size of lineages that potentially have distinct diversification rates." I think this sentence is not quite correct. When rates of diversification depend on the state, "standard" discrete character models (on which ancestral states depend) will fail: this observation is actually what motivated the development of the BiSSE family of models (see Maddison's 2006 brief communication in Evolution).

line 383: I don't know what the authors mean when they say "the character state is not polyphyletic." This statement should be clarified.
Experimental design: I have a few concerns about the description of the simulation procedure. In general, the description needs to be more explicit. For example, the authors state that (line 144):

"As this method produces trees with varying number of tips, we simulated 1000 trees each time and used the function tess.nTaxa.expected from the same package to select the best tree out of the 1000 trees. This was done by comparing the expected number of tips for every 1 unit time with the simulated tree using a correlation test. The tree with the maximum correlation coefficient was chosen as the best tree."

It is unclear what "each time" and "every 1 unit time" means. It's also not clear what the goal of the correlation test is, and how it is actually used: is it simply to pick the simulated tree that has the number of tips that is closest to the expected value?

Later, the authors describe varying the age of the tree (B_age) to obtain the targeted tree size (line 154). The authors should describe the motivation and execution of this procedure in more detail.

Because this study is primarily about the behavior of methods under simulation, I think it's critical that the description of the simulations makes it clear what the authors did, and why they did it. This section should be written with enough detail that a reader could recreate these simulations without having to look at the author's code. I also think that sections (1) and (2) can be combined into a single section, since section (1) exists solely to elucidate details of section (2)---the current ordering is a bit counter-intuitive.

2. Power

In Methods section (3), the authors describe computing the power as "the proportion of trees in which a significant rate shift was detected at the node where the subtree was attached to the basetree". However, it's not clear how this relates to BiSSE (which does not locate rate shifts, but rather tests for equality between state-specific diversification rates), or BAMM (which in principle could be used to test a hypothesis about a rate shift occurring on a given branch, but the authors do not describe what they actually do).

I would recommend that the authors explicitly state their definition of power for each of the three methods: for BiSSE, this will be a likelihood ratio test for equal or different speciation rates; for MEDUSA, this will be whether a multi-rate model is preferred and locates the rate shift on the correct branch; for BAMM, this will be some test that should be detailed (what the authors chose is unclear).

3. BiSSE analyses

Methods section (3a) describes comparing the unrestricted BiSSE model (lambda_1 != lambda_0, mu_1 != mu_0, q_01 != q_10) to a model where the speciation rates are restricted to be the same (lambda_1 == lambda_0). I am not sure that this is the right comparison: in the simulation, the extinction rates are fixed to be equal, so it is hard to imagine that the restricted model is the "true" model. It's not clear from the simulation what the "true" transition parameters should be equal or different, since the simulated data do not have rate shifts that are generated by a Markov process.

In any case, I believe the authors should explore some additional BiSSE models. In particular, I think the most relevant model comparisons are between (lambda_1 != lambda_0, mu_1 == mu_0, q_01 != q_10) and (lambda_1 == lambda_0, mu_1 == mu_0, q_01 != q_10). Because the "true" transition model is unclear, the authors might also compare (lambda_1 != lambda_0, mu_1 == mu_0, q_01 == q_10) and (lambda_1 == lambda_0, mu_1 == mu_0, q_01 == q_10). I would be surprised if these comparisons made much of a difference, but it feels odd to base the performance on two "false" models that assume the extinction rates for each state are unequal (mu_1 != mu_0).

4. Miscellaneous

Again, I find the use of "expected" (line 203) to be a bit confusing. The authors should simply call this the "true" asymmetry. For the asymmetry experiments, I also think that the authors should be computing relative error (as they do for their tip-ratio experiments) or percentage error for the asymmetry, which will make systematic patterns in the bias more obvious.
Validity of the findings: I have no real concerns about the authors' interpretations of their results.
Additional comments: This manuscript has improved substantially from the initial version. The research is well-motivated and timely, and will help a broad range of consumers of these popular methods interpret their results. However, I have a few (minor) outstanding concerns.

I would like to see the authors provide more explicit details about the simulation design and improve the clarity of their figures. There are a few remaining concerns with the data analysis section, relating to the definition of power and the choice of BiSSE models to compare. I provide more details for my concerns in the basic reporting and validity sections of my review.


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: SEED BANK AND GROWTH COMPARISONS OF NATIVE (VIRGILIA DIVARICATA) AND INVASIVE ALIEN (ACACIA MEARNSII AND A. MELANOXYLON) PLANTS: IMPLICATIONS FOR CONSERVATION
Review round: 1
Reviewer: 1

Output:
Basic reporting: No comment. Please see general comments.
Experimental design: No comment. Please see general comments.
Validity of the findings: No comment. Please see general comments.
Additional comments: Title: Seed bank and growth comparisons of native (Virgilia divaricata) and invasive alien (Acacia mearnsii and A. melanoxylon) plants: implications for conservation.
The manuscript is devoted to study the performance of two invasive alien trees in South Africa, Acacia mearnsii and A. melanoxylon, with that of an indigenous analogue, Virgilia divaricate. Authors analysed soil seed bank (seed densities, their vertical distribution, and viability) and growth rates (of seedlings and saplings), to determine potential for the native species to be used in management of the two invasive plants.
The manuscript include sufficient introduction and background to demonstrate the work fits into the plant invasive field of knowledge. Relevant prior literature are appropriately referenced.
At the end of introduction section authors state the aim of the study. The most important thing is that they seek to make a preliminary study and the data obtained support this objective. Said this, I consider the structure of the manuscript is not in adequate format:
The experimental design is so complex and the description does not allow a good understanding. I can understand the difficulty of explaining this kind of design. I suggest it be accompanied by an explanatory figure.
Figures accompanying the results are not self-explanatory. I miss a complete description in the figure legend as a description of the statistical treatment, meaning of ranked values and the representation of the statistical data in the graph, using letters and asterisks.
I have not clear why authors perform ANOVA in seed bank data and GLMs in seedling and sapling data.
In my honest opinion, I think authors argue largely in the conclusions section (it is not appropriate and not justified) and discussion section is so poor. I suggest merging it and writing a new and appropriate conclusion focused on the stated objective before and limited to the data supported by the results. When you rewrite this section, be careful of too speculative or inaccurate phrases like:
Pg. 13 Line 277-278 ‘Our estimates of seed bank densities were largely consistent with previous investigations (Table 1) and mirrored differences in seedling densities observed for the two acacias (Greet 2016; Tererai et al. 2015).’. Table 1 does not reflect this. The values of the literature are to a large extent higher than those presented in this study. This two references present indirect data about Acacia mearnsii and not for Acacia melanoxylon, by other hand the survey is in different ecosystems and variability, as was showed in this study, to high. Then this sentence is too speculative.
Pg. 15 Line 374-375 ‘The leaf litter of V. divaricata may also play a role in the prevention of Acacia germination, as A. longifolia germination was found to be reduced under V. oroboides litter but not vice versa’. It is too speculative for a conclusion. It would be in the discussion section and should be identified as such.
Pg. 16 Line 376-377 ‘To further decrease Acacia success, biological control (seed-boring weevils, flower-galling midges, and rust fungus; Impson et al. 2008, 2009; McTaggart et al. 2015) should be widely distributed. It is too speculative for a conclusion. It would be in the discussion section and should be identified as such.


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: SEED BANK AND GROWTH COMPARISONS OF NATIVE (VIRGILIA DIVARICATA) AND INVASIVE ALIEN (ACACIA MEARNSII AND A. MELANOXYLON) PLANTS: IMPLICATIONS FOR CONSERVATION
Review round: 1
Reviewer: 2

Output:
Basic reporting: I would suggest few improvements in the introduction. Firstly, would be interesting show clearly why the comparison among this species is important. Please, show how this comparison could improve the knowledge about biological invasion, competition, or plant management. Maybe transform your objective from comparison to hypothesis may help to achieve this recommendation.
You addressed competition in the introduction and I agree completely that your approach can contribute effectively in this field. However, I miss an explicit link between competition and the comparison among species performance. Growing and biomass are strongly related with competitiveness of plants and this could be a good way to conduct this link. Additionally, this link will also help to show the need to compare the performance between native and invasive species.
I would like to highlight the need going further in the discussion and explore better some references. You have a good example about how to use the reference to extrapolate your finds (line 374).
Several comments were done in the pdf file and will help the review process.
Experimental design: The methodology is appropriate, but few improvements are needed to make clearer. Details are given in the pdf file.
Validity of the findings: Conclusions are interested and have practical implications. However, few changes could increase the focus in the objectives of the study. Details are given in the pdf file.
Additional comments: Please, check the comment left in the Supplementary material S1.