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: ACTIVITY-SPECIFIC MOBILITY OF ADULTS IN A RURAL REGION OF WESTERN KENYA
Review round: 1
Reviewer: 3

Output:
Basic reporting: The article uses clear and professional English that is technically correct. The introduction includes relevant prior literature and an appropriate level of background information to couch the analysis in the broader field of knowledge on the topic of geographic access to resources, and questions of rural mobility. The structure of the article sections is standard. The research herein is self-contained and an appropriate unit of publication with reporting that does not extend beyond the reach of the hypothesis.

I have one small note for the introductory material - I suggest changing the instances of the word “affect” to a term that doesn’t so definitively imply causal relationships , for example “influence”, “shape”, “guide”, “impact” etc.

While the figures are relevant to the content of the article, I have a number of suggestions to improve them in consideration of clarity for the reader:

Figure 2: while the frequency charts give an overview of the visit frequencies for different activities, labeling the charts grey bar that matches the rest of the bars in color and orientation is visually confusing for the reader, especially for the top two rows of sub-charts where it’s not immediately obvious that the labels extend beyond the x-axis labels. I suggest labeling each sub-chart along the top. If the authors agree with this change, I further recommend changing subsequent figures to match this labeling style to maintain consistency (as is the current state with the vertical right hand side labels).

Figure 3: I suggest reducing the size x-axis labels so that it a) doesn’t overwhelm the visual content of the chart and for fig. 3 in particular b) so that it is more readable (you could also use the 45 degree labeling style for the duration labels on fig. 3). There is also something confusing  about the binning with ½ hours as reference labels – one suggestion is to clearly explain the binning (e.g., 5 minute intervals or whatever it is) in the article text where the figure is discussed, and to consider larger bins for better interpretability (even though the tradeoff is obviously coarser time representation).
Experimental design: Line 202 in the Results section: “We used the survey data to explore where people spent most of their time, how long they took to get there and how long they stayed when visiting places outside of the household.”, “we used the GPS data to explore the time participants spent outside of their households, and measure how variable overall movements were in our study population” (238), “ and “we also compared how well the survey and GPS data were able to capture the proportions of time spent at the different place types.” (252). These are all relevant and meaningful questions that can be answered with the data that were collected, however in my reading, these statements reflect aims that were not clearly stated in the introduction which reads “we use surveys and GPS trackers to compare movements to different types of activity for people in a rural area of western Kenya, including examining the links between resource access and demographic characteristic.” (line 98) I suggest reworking the final paragraph of the introduction to better define the research questions and aims of the research and very clearly state for the reader what they can expect you to report.
The descriptions of the data collection approaches were reasonably thorough and understandable, though I have a number of comments and suggestions relevant to the methods description and detail in the “Data analysis” section and beyond:
Line 174 “publicly available datasets” what datasets spsecifically? This should be included in data section before analysis.
Line 177 “A central GPS point was identified for each of the places, and a 25-metre radius around that point was used to determine when that place was visited by a person, defined as 5 minutes or more spent within that radius. Due to their larger size, a radius of 50 metres was used for town centres.” First, I am confused why town centres are mentioned as a grouping category (line 175) but then are never mentioned again in the text/results. Further, this could absolutely be a case of me misunderstanding the approach here and/or the rural context, but to me it doesn’t make sense to have a larger radius in town centres if you are using this buffer region to determine places of interest (POIs) that people visited – namely because I am picturing a “town centre” as an area that would have more potential POIs clustered more closely together. Is this not how the area is structured? If there are more POIs of different types (e.g., a health center and a place of worship in close proximity) then it would make sense to structure buffer radii such that they are sufficiently separate within the town centre.

At Line 182 you state, “We conducted univariable analyses using linear mixed models” and then in the title for Table 1 the description states “Univariable analysis of movement metrics using beta regression in a generalized linear model.” LMM sounds like an appropriate approach given the nested nature of the data (as explained), but beta regression in GLM is totally different – so which is it? Further, beta regression (in my understanding) uses proportional data as the outcome variable so what exactly would the proportion(s) tested be here if it was used (the results in Table 1 look like LMM to me)?

I understand the univariable approach singling out each location, but did you perform any analysis that included type of location as an explanatory control? It seems to me you could run one model on each outcome variable with all of your variables, including location type, as controls. If you didn’t try that, it’s worthwhile to explain in the methods section why you analysed each location type in isolation.

In terms of explanatory variables, many fewer variables are used in the models than what you gathered – how did you choose what to use and ignore? There should be some brief discussion that justifies your choices.

Overall, I suggest greater detail and clarity on the specific methods employed and justification for the approach.
Validity of the findings: This research is a worthwhile undertaking, and much of the reported results are relevant and appropriate to the (hopefully restated) aims of the paper. I have some suggestions to improve the rigor of the reporting:
A table of summary statistics for the demographics breakdown of respondents/participants is necessary to get an overview of your sample population. Also I would like to know how many participants were the livestock carers vs. the head of household w/ no livestock – surely this would come into play for the frequency charts at the very least when Livestock activity and water source might be influenced by those roles?
Line 224/table 1 – freq of visits, time spent traveling, time spent at places…if time spent traveling wasn’t significant when tested against the demographic characteristics, the non-significant results should still be reported. There is also the issue of the missing town centre place category.

Regarding GPS validation:
251 “Because the GPS data consistently underreported the absolute amount of time spent…” If you state in the background that surveys are subject to recall bias, and then state that an aim of this research is to compare surveys to GPS, this phrasing is problematic because you can’t say definitively where the discrepancy in time reporting occurs between survey or GPS. This fix could be something as simple as “…the GPS data consistently underreported the absolute amount of time spent compared to the survey reporting..” though take care to not overstate the quality and content of either survey or GPS because both are problematic in their own ways.

Fig. 5 and related discussion– line 256 “Other types of places were less accurately captured by the GPS data – specifically, time spent at places of worship and visits to other households and health facilities. Using a paired t-test we found significant differences in the mean proportions of time spent at other households and places of worship (p = 0.002 and p = 0.041, respectively) between the survey and GPS datasets.” It’s suspicious that places of worship, households and health facilities have poor correspondence between survey and GPS results as these also appear to be the only indoor locations that were studied (I’m assuming shops/markets are primarily time spent outdoors or around structures that wouldn’t completely interfere with GPS reception). Locations where you spend time indoors are likely to be subject to the most GPS outage/interference – how can you be sure that the result you found isn’t just a discovery of where GPS works (outside) and doesn’t (indoors)? I would suggest first, explaining in more detail how you handled GPS outages if they were present in the data. I see the linear interpolation for erroneous points that were deleted, but were gaps also filled this way? Perhaps gaps still accurately reflect the time spent in a location even if there isn’t a point at the expected resolution within the gap – either way, it needs to be explained.

Conclusions in the discussion are well-stated for the given results.
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: ACTIVITY-SPECIFIC MOBILITY OF ADULTS IN A RURAL REGION OF WESTERN KENYA
Review round: 2
Reviewer: 1

Output:
Basic reporting: I have no issue with how the paper is written or formatted.
Experimental design: The experimental design is acceptable.
Validity of the findings: Findings are valid based on the analysis methods presented.
Additional comments: I recommended accepting to publish the paper as is. I understand the limitation in providing maps as the author discussed due to privacy concerns for participants. Also, the authors responded well to the comments of other reviewers and improved as the original version.


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: ACTIVITY-SPECIFIC MOBILITY OF ADULTS IN A RURAL REGION OF WESTERN KENYA
Review round: 2
Reviewer: 2

Output:
Basic reporting: No comment
Experimental design: No comment
Validity of the findings: No comment
Additional comments: The authors have satisfactorily addressed my concerns with their revisions.


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: MOLECULAR CLOCKS, BIOGEOGRAPHY AND SPECIES DIVERSITY IN HERICHTHYS WITH EVALUATION OF THE ROLE OF PUNTA DEL MORRO AS A VICARIANT BRAKE ALONG THE MEXICAN TRANSITION ZONE IN THE CONTEXT OF LOCAL AND GLOBAL TIME FRAME OF CICHLID DIVERSIFICATION
Review round: 1
Reviewer: 1

Output:
Basic reporting: English requires a revision by a native speaker.

The authors did not clearly give credit for some of the ideas presented in their manuscript.

The article is poorly formatted and is not structured, the figures are poorly formatted, and not clearly described in the results section.

The data is shared, but their methods are not clearly described.

The article fails to clearly state the major advances with the previous studies published by the authors.
Experimental design: I found this a problem since they did not clearly state how this MS is original compared to the previous studies published by the coauthors.

The research question is defined but the tools used to resolved the question are questionable.

Some aspects related to giving credit to other authors ideas, as well as rigorously describe the background to their project is necessary. Finally, there are some major methodological flaws that require attention.

They need to better describe the methods.
Validity of the findings: Not a clear impact nor novelty on the study.

The study required to be improved in their analyses.

Several sections are very speculative and not clearly identified.
Additional comments: The authors used a combination of cytb and ddRADseq data, to carried out a species delimitation analysis and biogeographic analysis of the Herichthys genus. In particular, authors used the ddrad phylogenetic reconstruction to test the role of the Punta de Morro (PdM), as a vicariant event in the evolutionary history of the genus. While the Herichthys genus represents a very interesting model system to further explore species delimitation methods, I found the document with several organization problems as well as several methodological flaws (i.e. one maker instead of the genomic data in the species delimitation), that makes very difficult to understand the major advances in comparison with previous studies already published by the authors, then I did not found the MS particularly groundbreaking. Moreover, most of the findings were largely descriptive and the comparison with other studies at some sections were either vague or speculative. Finally, as I already mentioned one of the major flaws correspond to the use of only one marker in the species delimitation in comparison with the use of genomic data, mainly considering that the authors claim that the best phylogeny was recovered with the Radseq data. Beyond that, there are several studies that have pointed out the incongruencies between the gene trees and the species trees, mainly considering the authors' previous studies where they have suggested bias in the use of a single marker. Thus, due to the major issues I previously describe, I cannot recommend the MS to be published at PeerJ.

Here I include some major concerns, that I hope that can help the authors to improve their manuscript.

In general, I found the MS hard to follow, mainly because the document is not well organized, mixing the results with the discussion and without an order according to the methods section, making very complicated to understand the document, thus I strongly recommend the authors to carefully review and organize the document.

Additionally, through the MS the authors claim that the phylogeny of the Middle American cichlids is complete, “L117 The phylogeny of Middle American cichlids is now completely known based on complete species-level sampling and genomic phylogenies (Říčan et al. 2016)”, I found two problems with this statement, the first if that a phylogenetic hypothesis could be robust, but “completely known”, and moreover the authors fail to clearly stand for the advances of the document if everything is already known.

I found concerning that, in general, the authors did not give the credit to some of the ideas presented in their MS, but particularly important are the previous studies where the PdM has been suggested as a barrier for freshwater species (i.e. Contreras-Balderas, S., Obregon-Barboza, H., & Lozano-Vilano, M. L. (1996). Punta el Morro, an interesting barrier for distributional patterns of continental fishes in North and central Veracruz, México.). I encourage the authors to be more careful giving the credit to ideas suggested as theirs.

Either in the introduction as well as in the discussion, some general mechanisms or processes are not properly introduced, or is not clear how the authors could provide those analogies, making difficult to understand those ideas (i.e. A clear distinction between the central American cichlids and the North American cichlids is the conspicuous differences in the habitats, the first corresponds to the volcanic crater lakes, while the second ones correspond to a polymorphic groups which divergence have been clearly pointed in the plasticity directions.).

Methods
One major concern is that the authors did not follow an order between the methods, results, and discussion. Moreover, some sections of the methods are not clearly described, and a clear example of this was the poor description of the molecular clock used in the study, particularly, since the description did was in accordance with the result and figures presented. I strongly recommend the authors to clearly state how the run the molecular clock analyses, particularly describing if they partitioned the data matrix, which was the substitution model used for each partition, and how they apply the molecular clock to the ddRadSeq data.

By the other hand, the use of one mitochondrial marker to the species delimitation analyses was very confusing, since the authors used the ddRadseq data for the Biogeographic analysis carried out in this document. Moreover, in the document the authors claimed that the ddRad topology was the most robust and detailed, thus it seems contradictory to keep the less resolved and detailed topology in the delimitation analyses.

Additionally, there is large evidence that the use of mitochondrial DNA exclusively in the species delimitation could have some troubles (i.e. Brower, A. V. (2006). Problems with DNA barcodes for species delimitation:‘ten species’ of Astraptes fulgerator reassessed (Lepidoptera: Hesperiidae). Systematics and Biodiversity, 4(2), 127-132.) Maddison, W. P. (1997). Gene trees in species trees. Systematic biology, 46(3), 523-536.; Pamilo, P., & Nei, M. (1988). Relationships between gene trees and species trees. Molecular biology and evolution, 5(5), 568-583.)).

By another hand, at the biogeographic analyses, I found problematic the definition of the endemism areas, since in some cases they correspond to the same basin, thus it is not clearly stated how they defined those regions. For example, the authors divide the upper and lower Panuco basin under which criteria. Moreover, I consider very important to clearly stand which are the improvements-differences to the previous studies published in these biogeographic scenarios, that makes the current study and original contribution. Finally, authors should better describe the fundaments for some claims related to the biogeographic patterns, since some of them are clearly contradictory to previous studies (i.e. Rosen, D. E. (1975). A vicariance model of Caribbean biogeography. Systematic Biology, 24(4), 431-464.)

Results

In my opinion the results section is the less organized in the document, particularly because the authors did not state the major differences between their phylogeny (obtained with the cytb) in contrast to the ddRadseq topology, instead, apparently they used the ddRAdseq topology to describe the species recovered in both delimitation methods. I found this as the major flaw of the document since it is not clear which is the major advance compared to previous studies, and moreover, why did the authors use the ddRadseq three to described their valid species, if the species delimitation was carried out with the cytb data. Thus, the species delimitation results seem unnecessary ambiguous in terms of which are the major differences with the previous published data.

Species delimitation results are poorly described, particularly since the authors claim some differences between the two methods used (e.g. 476-481), but those major differences were not accurately described, making confusing to understand which figure 2 or 3, the one describing the major differences across the methods. Additionally, authors did not accurately describe why they used the Radseq topology to present the valid species. Moreover, Figure 2 was not accurately described since on it least three alternative taxonomic proposals appeared but they are not clearly described in the document.

It is not clear how the authors could suggest that they apply a molecular clock using the ddRadseq data (L387-393), thus this is very important, since they need to clearly describe how they construct apply the molecular clock to the Radseq data, this is particularly important considering that it is not possible to assign a mutation rate to SNPs data.

In general, the results section resembles more a discussion section, were repeatedly the authors contrast their results with other studies, or even give some explanations to the patterns found.

Discussion
Similarly to the results section, the species delimitation and the biogeographic scenarios are commonly mixed, making very complicated for an unfamiliar reader understand the scenarios described, and the hypotheses tested. Moreover, most of the major conclusions in the document make reference to the previous results presented in Říčan et al. 2016, making very difficult to understand the relevance of the present study.

Similarly to the introduction, at the discussion authors commonly introduce some points that have not been properly defined, as “the ecomorphological polymorphism within an species group” (ie. L487), or “deep clades” (ie. L488), this makes even more vague the arguments related to the diversification of the group, making most of those sections speculative.

The authors suggest that “Further studies including independent genomic data with a robust locality sampling are thus necessary to provide hypotheses of species boundaries (Zhang et al. 2011).” could help in the species delimitation hypothesis, however, the authors did not use the genomic data that they have previously published, instead use one marker (cytb).

The authors claim a circular reasoning in dating, particularly in the Herichthys genus but also in other studies carried in the region to other groups, particularly for the case the Astyanax (Ornelas-García et al. 2008), the authors did not only used the PdM as a calibration point, thus, I encourage the authors to clearly describe the methods carried out by other authors, in order to avoid misinterpretation of the published literature.

It is not clear why the authors include the Caribbean in their discussion since the group under study is not distributed in this region, all this section is not part of the methods, and apparently the authors used previously published data to describe this section, thus it did not correspond to an original contribution.

Minor comments,
“The transmexican volcanic belt particularly is not a lava flow. It is the PdM (Hulsey et al. 2004, 2010),” : This is not the correct citation.

Perdices et al. 2002 neither Martin and Bermingam 1998, studies were not carried out on Cichlids.


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: MOLECULAR CLOCKS, BIOGEOGRAPHY AND SPECIES DIVERSITY IN HERICHTHYS WITH EVALUATION OF THE ROLE OF PUNTA DEL MORRO AS A VICARIANT BRAKE ALONG THE MEXICAN TRANSITION ZONE IN THE CONTEXT OF LOCAL AND GLOBAL TIME FRAME OF CICHLID DIVERSIFICATION
Review round: 1
Reviewer: 2

Output:
Basic reporting: With regards to how the information is present in the paper, there is a lot of information that sometimes is confused and probably needs a reorganization that will improve the understanding of the whole manuscript. The amount of data reported in this manuscript is very valuable but complex to organize. Just need to be rewritten in some areas. English language is very correct along the manuscript.

In my view, if I am not wrong, the paper has two main goals: (1) to understand the diversity and historical biogeography of the genus Herychthys due to its strategic geographic position relative to the Punta del Morro formation, and therefore, to testing the importance of this biogeographic event in the evolutionary history of cichlids (Huelsey et al., 2004, 2010). And (2) to evaluate the global diversification of Middle America cichlids by analysing previous on previous ddRAD or mitochondrial-dominated published data (Rican et al., 2013 and 2016). In the introduction section information is well organize (from general to particular: general context for divergence patterns and biogeography of cichlids, PdM and Herichthys as the only cichlid group north of PdM point and the group that may shed light in improve our knowledge about Middle America cichlids due to its geographic position). Nevertheless, at the end of introduction (lines 188-193), authors wrote “In this study, we thus focus on two topics; I) on species diversity analysis within Herichthys … II) on the biogeographical and temporal aspects of Herichthys diversification. For the second goal, we place these aspects of Herichthys diversification into a wider Middle America and global cichlid diversification…”. Please rewrite this last paragraph to make it more consistent with the whole introduction. However, in the Material and Methods and the Results sections information is more difficult to follow and sometimes it is not clear what data set authors refer. Results section is mainly focussed on Herichthys and PdM and no much information about global Middle America cichlids biogeography is reported. Moreover, there are some sentences in Results section that should belong to Discussion (e.g. lines 400-404; lines 417-421…). And, conversely, Discussion is also well structured and easy to follow in its present form (from particular Herichthys and PdM to global diversification of Middle America cichlids). Please, give a look at the manuscript and rewrite Results sections to organize such high and interesting amount of information. I miss also some comparison of species delimitation based on cytochrome b performed here and previous nuclear phylogenies (ddRAD; Rican et al., 2016).

Supplementary material provided is very adequate and complement results when necessary

Minor concerns:
-The title is too long, I suggest authors to shorten or rewrite it.
-Line 75: change “Tagliacolo” by “Tagliacollo”. By the way, this cite is not included in the reference section. Please include it.
-Line 99: Change “have divided” by “have been divided”
-Line 134: Change “2013,;” by “2013;”
-Line 202: “142 haplotypes”…. Line 339 “133 haplotypes”. Please review these numbers
-Lines 291-292: “The bPTP analysis was run both on the MrBayes tree and on ultrametric BEAST tree in order to compare results”. However authors do not indicate they run MrBayes in other sections of the manuscript.
-Line 386: Highlight this line as subtitle
-Line 387: Change “Fig.ure 4” by “Fig. 4”
-Lines 656 and 658: Change “t0” by “to”
-Line 659: Change “this events” by “these events”
-Figure 1. Please, include scale in the maps of Figure1.
-Figure 2. In my view, in the caption of this figure the sentence “the calibration by the Punta del Morro (PdM) is clearly an outlier (…) the PdM calibration analyses (analyses I-IV)” should be removed. I think it does not bring necessary information to this figure
-Figure 4. Letters from phylogenetic tree are not readable in printed version. For instance, in lines 451-452 authors said“… contemporaneous extinctions among the lowland genera (…) Vieja and Maskaheros (Fig. 4…), but it is very difficult to find this genera in the Figure 4.
Experimental design: This manuscript mainly constitute an original primary research that fit with the aims and scope of PeerJ. In general methodology used is adequate to solve the questions proposed by authors. Methods applied to reconstruct divergence time estimations, one of the key point of this manuscript to understand the evolutionary and biogeographic history of the Middle America cichlids, is described with sufficient detail. Information about used specimens is complete and present in Supplementary Material.

Nevertheless, focusing on analyses, I have several main concerns that should be addressed. One of these main concerns is related with phylogenetic analysis. Authors used Maximum Parsimony (MP) to infer phylogeny, however this methodology is not adequate for this purpose. MP analysis ignores branch length, associated to probability of evolutionary change and assumes that changes between nucleotide are independent (Yang, 2006), i.e. parameters of the evolutionary model cannot be incorporated in the analysis. Therefore, phylogeny may not be representing accurate relationships. I suggest authors to run Maximum Likelihood (additionally to the Bayesian Inference they carry out), in which parameter models may be incorporated, and remove Maximum Parsimony from the study.
Regarding Bayesian Inference run in BEAST, authors state “… MCMC simulations was run for 10 million generations… (Line 236)” Do authors get convergence with this number of generations? For BEAST analysis a chain of 10 millions of generations is often too short (usually enough to get convergence in MrBayes). And do authors just compare the four independent analyses they perform or do they combine them? Please clarify.
Another major concern that I have is related to molecular clock analyses in this study. I would eliminate PdM calibration in the analysis V (which is based on geological calibrations) and leave only the other two geological calibration points in order to avoid the influence of PdM calibration in the result of this analysis (line 383-385). Authors later discuss well about this circularity, and they have performed one analysis using only the PdM point as calibration (VI), which is necessary to test the biogeographic hypothesis of vicariance driven by “Punta de Morro”. Therefore, I would eliminate this analysis V. Moreover, for these BEAST analyses authors do not explain the number of generations they run for each of the four independent analyses that they later combine in LogCombiner.
An additional question that is raised regarding molecular clock analyses is the number of individuals that authors consider in these analyses. Have they included the whole data set or have they selected some individuals? This is very important to be notified because its influence in the speciation/coalescent tree prior. Authors used a “coalescent model with constant size” as prior for dating analysis (Line 246). Coalescence priors should be correctly used within a species, but authors have different species and their populations within the molecular clock analysis. Therefore, coalescent tree prior may bias results, as well as using a speciation prior, which could be overestimating speciation events. The best way for integrating both scales (species and populations) in BEAST software is to use the option STARBEAST (Heled & Drummond, 2010) that takes into account coalescence within the speciation (Yule) process and that render both species-tree and gene trees. Nevertheless, although possible, this approach is more adequate for multilocus dataset than for only one gene (cytb) due to error in date estimations may be higher in one-locus analysis. STARBEAST also tend to provide more recent divergence times than a “standard beast” when estimates the species-tree. For this reason I recommend authors to run STARBEAST for the six calibration analyses using the partition by codon cyt b and discuss results of the cytb b gene tree obtained from these analyses, which would have incorporated coalescence within the speciation process.
Validity of the findings: The paper of Perez-Miranda et al. is a great contribution to the knowledge of the evolutionary patterns and biogeography of freshwater fish of Middle America and Caribbean Region. The debate about the colonization of Middle America - Caribbean region and the relationships of their biota is still open, especially focus on when started the presence of permanent emerged lands in this region (e.g., among others, GAARlandia hypothesis; Iturralde-Vinent and MacPhee 1999; Iturralde-Vinent, 2006…) and authors provide here, with this study about the cichlid genus Herichthys, a new piece of this interesting puzzle. This paper also highlights the importance of having several accurate calibration points to obtain a robust historical biogeography of any particular taxonomic group. This paper deserves to be published in PeerJ after authors deal with major concerns I have and that I have previously reported.  Therefore, I encourage authors to deal with these major concerns in order to make suitable this manuscript for publication.
Additional comments: No additional comments


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

Input:
Title: MOLECULAR CLOCKS, BIOGEOGRAPHY AND SPECIES DIVERSITY IN HERICHTHYS WITH EVALUATION OF THE ROLE OF PUNTA DEL MORRO AS A VICARIANT BRAKE ALONG THE MEXICAN TRANSITION ZONE IN THE CONTEXT OF LOCAL AND GLOBAL TIME FRAME OF CICHLID DIVERSIFICATION
Review round: 2
Reviewer: 1

Output:
Basic reporting: This is the second time that I have reviewed this manuscript and I have to say it has been improved a lot by authors. They have solved my main concerns about dating analyses and calibration points, as they now have analyzed "Punta de Morro" calibration alone in order to compare with the remaining calibrations. The inclusion of PdM along with other calibration points within the same analysis in the previous version of the manuscript was biasing results and made difficult to extract accurate conclusions from them. In fact, now "Methods" section is clearer and well-organized than before. At the same time, now it is also clear to me how authors incorporate the Rad-seq tree topology of Oldrich et al 2016 in the biogeographic analysis, which was not easy to follow in the previous version of the manuscript. For this reason, I consider the manuscript is now prepared to be accepted in PeerJ. Although I still have some minor concerns regarding analyses that I explain in the "Experimental design" section and that should be revised. Authors also should do a proofreading of the manuscript as I have found some typing mistakes.
Experimental design: This manuscript constitutes a primary research that fit in the Aims and Scope of the journal and provide a robust background about the diversification of cichlids and particularly for the genus Herichthys. In general methodology used is correct and adequate to solve the proposed evolutionary questions. I just still have a minor concern about the selection of the evolutionary model used for phylogenetic performance. Authors say that they used the GTR+G+I model, but they do not specify any software to do that, such as jModeltest of PartitionFinder. Why did authors use this model? Is it because it is the most complex model? There is a debate about the use of the most complex model and the overestimation of parameters if this model is not the adequate for the data or the non influence of the complexity of the model according to different authors. In my experience and knowing this fish group the selection of the model is not going to affect strongly to results, it would be more elegant that authors estimate themselves the best-fit model for these data. The same is about the use of Beast, a coalescent model is not adequate when different species are included in the analyses, and would be more correct to used an speciation prior (Yule or Birth date), taking into account that in that case just one sequence per species should be keeping in the analyses. However, using StarBeast is correct when the data are constituted by species and populations (or several individuals per species), as is the case of this study, due to this approach is able to integrate speciation and coalescent processes in the same analyses. I do not understand either why authors used a relaxed molecular clock prior in Beast and a strict clock in StarBeast, have the tested this statement?. Please, clarify. My recommendation is that authors used only StarBeast analyses (even if they only have the cytochrome b marker), in this case they can estimate the species tree and the gene tree at the same time. These are the minor concerns that I have for this manuscript and those that should be taking into account before the acceptance of the manuscript.
Validity of the findings: This manuscript is of interest to the scientific community due to the importance of cichlid fish as model for evolutionary and biogeographic studies. The manuscript is also testing the influence of a biogeographical barrier that have been consider as promotor of vicariant patterns in different organisms. The finding of this study suggest an older diversification for cichlids in comparison to other studies and authors provide robust data for support this conclusion, which is also well developed in the Discussion section. They also provide a more complete phylogeny for the genus Herichthys, showing the need of a systematic review of the group.
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: THE PREDICTIVE VALUE OF PRDM2 IN SOLID TUMOR: A SYSTEMATIC REVIEW AND META-ANALYSIS
Review round: 1
Reviewer: 1

Output:
Basic reporting: The authors undertake a comprehensive analysis to identify if down regulation of PRDM2, a member of the nuclear histone/protein methyltransferase, can serve as a biomarker in early cancer diagnosis.
Experimental design: The study is well thought through and critical of itself. I applaud the authors meticulous and tedious work. I'm in favor of publication as it insights need for more experimental studies on PRDM2 down regulation in solid tumors.
Validity of the findings: the authors should explain in the results how the 3870 records were excluded and they should make conclusions once there is sufficient data available otherwise it appears to be phrased as if authors doubt their own conclusions in their present study.
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: THE PREDICTIVE VALUE OF PRDM2 IN SOLID TUMOR: A SYSTEMATIC REVIEW AND META-ANALYSIS
Review round: 1
Reviewer: 2

Output:
Basic reporting: The predictive value of PRDM2 in solid tumor: a systematic review and meta-analysis by Tanadi et. al., is a nicely written review presenting a meta-analyses and investigating the potential of PRDM2 downregulation as a diagnostic biomarker in solid tumor. There are no grammatical errors and the writing is crisp. The figures and tables are of high quality. The review addresses important questions and findings pertaining to relationship between PRDM2 and solid tumors and I think it will be of general interest to a reader in cancer research. I have highlighted few important points, which, I believe, need to be addressed before the manuscript is deemed fit to be published in PeerJ.
Experimental design: Within aims and scope of the journal.
Validity of the findings: Meets standards. I have listed a few points in the next section which I believe need to be addressed before it makes it into PeerJ.
Additional comments: Line 61-63: Can the authors give a new recent reference if it is available. Or is the 2018 reference the latest?

Line 66-68: Can the authors comment or add few lines on why the implementation in clinical setting is lacking? It would be of general interest to the reader. For example, highlight the bottlenecks that prevents biomarker discovery translating into clinical setting.

General question pertaining to the Introduction: What is rationale behind selection of PRDM2 for this study over other candidates. Also, cancer is a very broad term. Which specific types of cancer are associated with PRDM2? Or is it a universal biomarker for all cancers?

Line 105-107: “Each step of the process was performed by two independent reviewers (AB and IPW), and any differences were solved through a discussion” – This line seems confusing and I think it’s better to omit this line from the manuscript because the search criteria has been elaborated in the first and third paragraphs of the sub section.

Line124-126, Line 154-155: Similar to the previous comment, the author contributions can be listed at the end of the manuscript. Listing them inside the actual text is not a preferred way.

Line173: Could the authors comment on when they mean by “studies being irrelevant”?

Line 181-184: Why is there so vast difference between the sample size and the control size?

Line 274-277: The authors state that PRDM2 downregulation occurs in solid tumors. What do the authors mean by saying they could not find relationship between PRDM2 and several solid tumors such as neuroblastoma, breast cancers, melanoma, parathyroid adenoma and Merkel cell carcinoma? Is the downregulation? Or no expression of PRDM2 at all? Also, it would important to specify which type of solid tumors show downregulated PRDM2.

Line 286-297: Have the authors tried to analyze whether PRDM2 downregulation can be used as potential diagnostic biomarker in particular type of solid tumor i.e what happens when you don’t group all the solid tumors, what if you analyze solid tumors (for example breast, lung etc.) independently?

Line 315-317: Are there no studies that have used RT-PCR (for example), to quantify the levels of PRDM2 in normal vs solid tumors?


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: PERFORMANCE IN A NOVEL ENVIRONMENT SUBJECT TO GHOST COMPETITION
Review round: 1
Reviewer: 1

Output:
Basic reporting: This manuscript is well-written and professional. Most of the text is easy to comprehend. Though the experimental design is very good, it is also very complicated. I had to read this several times to fully understand exactly what was done here. The methods would benefit from a diagram showing the different evolutionary environments and the current ecological environments.
Some of the references in the text are not listed in the references at the end.
Experimental design: The manuscript proposes an interesting question to be tested, namely, do competitors (different mite species) affect selection to a novel environment (in this case, the environment is the plant on which the mites grow). Moreover, they serendipitously are able to examine the effect of ghost species...those that are in the community for some time and affect community or population (or evolutionary) dynamics, even though they are not a part of the final community. The design is a good one for testing the question posed. As stated above, the design is complicated and would benefit from a summary diagram.

-There is one statistical table presented, though other tests were also performed. These should be included in the main text as well. Perhaps it is because violin plots were used, but the statistical results do not seem to support what is shown in the graphs. I think violin plots may not be the most useful for demonstrating differences between treatments, but this also makes me question many aspects of the statistical design. Were Blocks included as a factor in all analyses? It seems as though they were in some, but not others, but this may just need clarification. The same can be said of Day. I could not tell in which analyses Day was included as a factor, or fecundity was averaged across days. This deserves some clarification or reanalysis.
Validity of the findings: Although I very much like the ideas being tested here and am excited that somebody is testing the effect of ghost species on evolution (seriously, I really like this idea!), I completely disagree with the conclusions.
First, the authors conclude that the presence of an interspecific competitor affects evolution in response to a novel environment (cucumber plants), but I do not see any evidence for that. They seem to base this conclusion on Fig. 2b, where they claim the density of competitors in the selection environment affects fecundity in the novel ecological environment, but that stats do not support this conclusion. There is no significant difference between the 0 interspecific competitors and any of the other densities. The only significant difference is between zero competitors and the plot on the right, though despite a lot of time trying to figure it out, I can't figure out what treatment this plot represents. It doesn't appear to be on the same x-axis as the other violin plots, or if it is, I do not understand how the highest density of competitors can be in the "no comp" treatment.
Second, the authors conclude that the "ghost" species has an effect on evolution, but I disagree. Any competition experiment that tracks growth over time would expect that when one competitor is removed (as one mite species here goes extinct after two months), the remaining species would increase in abundance, and that this increase in abundance will take some time. The same happen here. The ghost species has a temporary effect that, when removed, the community takes some time to recover from. I would not expect anything different. I would only consider this an effective ghost species if the effect were permanent and stable. At least that is my understanding of ghost species from the terHorst, Burns, and Miller paper. What is shown here is just a transient effect of competition.
Finally, there is a lot of focus here on the possible effects of genetic drift, though I am not sure why this is given so much attention. If one finds a difference in selection environments, with replicates within those environments, that indicates that selection had an effect that must have been much stronger than any effect of genetic drift. The authors are to be applauded for considering drift and the effect of abundance, but given that it has so little effect, I do not think that they need to spend much space discussing it. In that sense, Fig. 3 is not necessary.
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: PERFORMANCE IN A NOVEL ENVIRONMENT SUBJECT TO GHOST COMPETITION
Review round: 1
Reviewer: 2

Output:
Basic reporting: I really enjoyed reading this manuscript. The authors communicated in clear unambiguous, professional English. In terms of the amount of background information, I feel that the authors have done a sufficient job with what they have reported and discussed, but ultimately that they ought to reframe their manuscript, and so will have to find the relevant literature for that. The figures are nice and easy to follow.
Experimental design: I think the results of this study are very interesting, and while I appreciate that the authors attempted to make something out of what others may have considered a failed experiment, I think that the way they did this is not great and that the manuscript requires some reframing.

1. the experiment was not initially designed around testing the effect of ghost competition. While this may be an explanation for their results, I feel that it is disingenuous to use these results a test for that. I would reframe this manuscript to test their initial hypothesis, then in the discussion suggest ghost competition as one possible reason for observing the results that they did.

2. The authors used inbred lines of mites, and did an evolutionary experiment with them. Was there enough genetic variation in the population to allow for evolution? If the T. urticae population evolved initially, perhaps there wasn’t enough genetic variability remaining for it to evolve again after the extinction of T. ludeni, and that the long term results seen (25 generations) are due to this, rather than lasting effects of ghost competition.
Validity of the findings: This is covered under experimental design.
Additional comments: Overall, I did really enjoy reading this paper and found it interesting. In addition to my comments above, I have some minor comments that I refer to by line numbers:

Line 30 - populations are the unit for evolution, not species. I think this sentence would be improved by rewording.

Line 26 - the word “even” does not need to be italicized. But also, could be removed entirely and the sentence would be better.

Line 89 - I don’t think it’s necessary to say that it’s an underestimated process (compared to what?). This sentence could be rewritten as “We therefore suggest that ghost competition may lead to differences in long-term local adaptation.”

Lines 213-214 - Repetitive text?

Line 393 - replace “are affecting” with “affect”

Line 407 - replace “we did find” with “we found”


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: PERFORMANCE IN A NOVEL ENVIRONMENT SUBJECT TO GHOST COMPETITION
Review round: 1
Reviewer: 3

Output:
Basic reporting: The English is decent, but sometimes feels awkwardly worded (for example, line 158, 160-166; see “general comments”). Several aspects of the experiment were not well explained, notably what “host islands” were (used but not introduced on line 126), and the distinction between replicates and host islands (was there one?). Experimental design involved insects on two different host plant species, with fecundity evaluated on two different host plant species, and it was sometimes difficult to tell which of those were being compared (e.g. insects from the same host plant species evaluated on two host plant species, or individuals from each host plant species evaluated on different host plant species). This is inherently a difficult distinction to get across, and some careful rewording is in order in some cases (see general comments for examples).

Figure 1B has erroneous confidence intervals, and letter groupings are not explained. This may also be the case for figure 2, which appears to use the same code. The black lines of figure 3 are identical to those used to represent 95% CI in other figures in this paper, yet instead represents range of the data in this case (which we can already see as the raw data is all present in this figure); this may confuse readers.
Experimental design: The research question is a good one – how does the presence of a heterospecific population influence the evolutionary trajectory of a population. The experiment was carried out across 10 months, and tracked performance of populations using the fecundity of the standardized grandchildren of 5 randomly sampled individuals per time point. The experimental design introduces a number of complicating factors, including (a) differing population sizes between intra- and inter-specific competition treatments, (b) regular “disturbance events” in which new plants were added and old ones were removed, necessitating colonization, (c) the use of fecundity in the absence of competition as a proxy for fitness (typically we think that performance at high densities determines competitive abilities), and (d) using a sample of 5 individuals at a time point as a proxy for the total population, when each replicate started with 13 distinct genotypes (isofemale lines). I note that some of these factors are necessitated by the system and the overall type of experiment (it is impossible to simultaneously control population size, patch size, and overall density), and experiments in ecology are often necessarily messy.

The statistical analysis leaves me with several concerns. First, the model choices seem prone to overfitting – in particular, treating the 10 months as a categorical predictor, and then allowing interactions between that and other factors in addition to nested random effects leads to a substantial number of estimated coefficients. The authors report running into issues with singular fits, which I also experienced while fitting simpler models to test their observation that T. urticae evolved to have higher fecundity on cucumbers when early T. ludeni populations were higher. One explanation for that would be that, with only 8 replicates for this treatment, early T. ludeni population size might largely be serving as a stand-in for island identity. Second, effect sizes are not reported, and the values in Table 1 are not in the raw units despite their description. Third, the statistical analyses are exploratory – this is fine, but p-values lose their meaning when calculated after model selection. In essence, by testing many potential predictors (for example, “initial” densities of each herbivore species crossed by host plant species) and focusing only on those predictors that model selection identifies as important, we risk capturing spurious relationships and elevating them to statistical significance.

Trajectories of population densities through time across ~25 generations are fit using a quadratic model (line 241) – this is not something we would expect biologically or phenomenologically, and while it is not the emphasis of this paper, I do not think this is the correct approach to take.  It would be more appropriate to (a) use existing models for population growth (for example, logistic growth), or (b) use flexible methods like penalized spline-fitting. I would focus on (b), as (a) requires choosing the correct functional form for population growth in this system. On the other hand, (a) can provide estimates of biologically interesting quantities like carrying capacity (although note that with the weekly colonization/plant removal process, interpretation of model parameters is complicated). By fitting a quadratic equation, you are implicitly assuming that growth itself is quadratic through time. One of the issues of quadratic equations is that they have a constrained curvature - for a trajectory to increase more steeply early than it does late (e.g. density-dependent growth behavior), the model necessarily will include a negative quadratic coefficient, which will ensure that for a late enough time, the population size will go into the negatives. We see the start of this with the projection of T. ludeni (no comp) at the end of the study in Fig. 1A, and the reverse problem with T. ludeni (comp) right as the projections are cut off (the line is starting to point upward, and would trend towards infinity with increasing time).

More generally, if the question is the long-term effect of “ghost” competition on population fecundity, it seems that the most important measure is the population behavior at the end of the experiment, not midway through. Further, since all replicates within a treatment began with (hypothetically) identical starting populations, the relationship between early population sizes and later fecundity are correlative, and may reflect some latent variable(s) determining island quality.
Validity of the findings: The data is provided but lacks the metadata to explain what the various columns are. Two column in the data frames include the filepath of the original photos on the author’s computer, which do not appear to have any use to readers. These and any other truly extraneous columns (X, which appears to be row numbers from a past data frame?) could be removed.

As mentioned above, I have concerns with the statistical methods, and the results that derive from those do not feel statistically sound. In some cases, the authors provide statements that do not appear to be supported by the data (e.g. on line 359 the others suggest that selection pressure of conspecifics is higher than heterospecifics in this experiment, but I am unclear the evidence; see General Comments for any other cases). In several places the authors present predictors as having no effect when they mean that the predictor was not included in the best-fitting model – a subtle distinction, but one worth making (e.g. line 292-293, the best-fitting model did not include time, but this does not mean that the effect is stable through time, see General Comments for a few more examples). The key results of this study are several layers removed from the claims of their conclusion – the impact of the ghost species was detected when pooling all time points, but was not detected (at least not when I tried with their data) when looking at the latest time points.
Additional comments: Throughout the paper, the authors use “initial” densities to refer to population densities averaged (or summed?) across the first two months. I would suggest using a different word, as the actual initial population sizes were the 52 individuals at the start of the experiment.

Analysis of the effect of competition on population density seem to ignore the fact that each species started with half as many individuals in the competition experiments (e.g. line 297). We would expect that with half the initial population size, subsequent population censuses should be quite different (at least until density dependence evens things out).

This is a system with repeated disturbance; in general there are expectations that disturbances may enable coexistence which otherwise isn’t possible. Colonization, while important, isn’t a fundamental part of much of coexistence. I would like to see some explanation for how you think this might/might not matter.

This paper is focused on explaining adaptation, suggesting that performance (in this case fecundities) can change through time. I think it would be appropriate to think carefully about when it’s appropriate to pool samples across time and when it’s not. Whatever choice the authors make, they should justify it to the reader.

MINOR COMMENTS

Line 35: Niche overlap is an idea that predates Bolnick 2001, and it might be appropriate to cite a more foundational paper as well.

Line 49: I’m surprised there aren’t earlier references than this; this seems like a specific case of coexistence theory.

Line 52, 62, possibly later: replace “coexisting” with “co-occurring”. Coexistence implies indefinite persistence of each species (see Siepielski and McPeek 2010, “On the evidence for species coexistence…”).

Line 56: this paragraph feels a bit jarring in that, as you found, interspecific competition can also simply cause extinction of one of the species. This extreme hindrance to local adaptation seems like it should be addressed rather than ignored.

Readers working in the plant-insect interactions world are likely to be thinking about plant induction, both as an effect that can change through time and something that can mediate interspecific interactions. You mention this in the discussion, but it seems like it would be valuable to address this sooner, perhaps in the introduction and/or methods.

Line 126: the term “islands” is used here and then throughout the paper, but never explained.
Line 134: I wouldn't call this natural movement dynamics. I think this section should be revised a bit. I'm on board for what was done, but the explanation felt lackluster. I would reorder to start by explaining the biology, and then walk through the plant addition/removal methods.

Line 152-155: Uncontrolled and undetected inconsistency in selective pressures between replicates isn't good in general, and especially when there are only 8 replicates total. It’s good to acknowledge it, but don’t refer to it as a benefit.

Line 158: “rather” is an informal word choice

Line 160-166: The wording here feels awkward. I would rephrase a bit to focus on the things you kept constant, then mention "this necessarily meant that the initial population size for each species was not the same across the different treatments; we recognize this may effect genetic drift and sampling effect".

Line 174: how does the every-two-week-sampling line up with the plant replacement scheme? How long did mites have to colonize the new plant before counting?

Lines 201-203: English is awkward

Where did the leaf disks in fecundity testing come from? Was anything done to account for induction in them?

Line 207: providing the error distribution without the response variable seems odd. Were you using the same distribution for population densities and fecundity measures?

Line 210: Typo – “parameterization”.  Also, do you have a citation for this?

Line 219: If you’re using glmm, you were presumably including random effects. You should mention this here. In this case, because you have a total of 2 predictors, each of two factors, it would seem most appropriate to carry out an ANOVA comparison of the full model rather than carry out model selection.

Line 234: What does the result look like if you treat time as a continuous variable, though? If they are similar, report that. If not, report *that*. Breaking a continuous variable (time) into many factors is inherently concerning, and while your explanation makes sense, readers will be more comfortable knowing that you tried the simpler approach.

Line 241: This deserves its own (sub)section, as it appears to be the only analysis using population density instead of fecundity measures. This is also the only section in which time is treated as continuous instead of categorical.

Line 271: if T. ludeni reached significantly lower density than T. urticae, this could still reflect host plant problems (since this was not a choice experiment, and performance is not binary). We would expect to see a gradient in performance from good hosts to bad hosts to unusable hosts, much as we see with patch quality when looking at source-sink dynamics.

Line 298: these appear to be equilibrium densities, but we haven’t established this (and technically a quadratic model has no equilibrium density)

line 325-328 presupposes that the mites are at or near the carrying capacity – without a model that includes carrying capacity, this is hard to support.

unclear what 336-338 is referring to

Wording on lines 346-348 is a little unclear - make it obvious to the readers that in both cases you are talking about fecundity on the novel host plant. (Currently it can be misinterpreted as the T. urticae that evolved on the novel host plant have higher performance on that plant than the control population has on the control plant).

Lines 349-351: this is possible, but it could also be that mites have a tradeoff between their ability to perform on the plant vs their ability to compete with heterospecifics. It would help to know the extent to which mites compete by directly interacting, vs through resource competition.

sentence starting on line 354 is incomplete.

Line 359: What is our evidence for the selection pressure of conspecifics being higher than heterospecifics?

Sentence starting line 372 can be tightened up.

Wording on line 399-400 is a bit confusing. You mean that there were not control populations on beans? Use of "mixed" confuses things.

Fig 1:
•	(A) What models were used to fit the data? It appears this was not done using the modeling of the methods section, and instead uses ggplot methods.
•	(B) I thought we did not have controls on beans? This is performance on both hosts from control populations raised only on cucumber?
•	(B) Confidence intervals for Fig 1B appear to be extremely wrong. Significance groups look good, but CIs in the figure do not at all match (a) significance groups, or (b) CIs when I calculate them. Sample code to make plot (which does not match Fig 1B) and calculate differences of groups (which matches paper results):
####
test=data.frame(total=control_data$Total, mp=control_data$MitePlant)
out.lm=lm(total ~ mp -1, data=test)
## note: this is ordering groups a bit differently - by mite and then by plant.
ci=confint(out.lm)
plot(1:4, out.lm$coefficients, ylim=c(0,100), pch=19)
segments(x0=1:4, y0=ci[,1], y1=ci[,2])
out.aov=aov(total ~ mp, data=test)
TukeyHSD(out.aov)
####

I found it interesting that the fecundity had a downward trend through time in both cases, with month as a continuous variable being a significant predictor of fecundity in the bean data.

Fig 2: by "minimal model" do you mean "best-fitting model"? Minimal could mean many things, including intercept-only.

Fig 3c: No data points for replicate 7? If so, remove from the figure as was done in fig 3a
What is the distinction between island and replicate?

Line 292-293: finding the best-fitting model did not include time does not mean that the effect is stable through time.

Lines 293-294: tell us the evidence for this.

CODE COMMENTS:

Note that the normal distribution appears to be almost as good a fit as the negative binomial, and the overdispersed negative binomial (which is the distribution used in model fitting) is not one that is evaluated during the distribution testing of "Dynamics and performance of the ghost competitor" section. lm(Total~TreatPlant*MiteSp, data=control_data) performs substantially better (AIC = 820) than the stmodel.0 (AIC = 840), suggesting that the simpler normal distribution may actually be more appropriate here.

In general, I would use and present the simplest test possible for the relationship in question. For example, the relationship between “initial” density of T ludeni and fecundity of T. urticae could be evaluated with a simple lmer model, of lmer(Total ~ initialdensL + (1 | CombinedName), data=cucumberdatacomp). In doing so, we find that there is a singularity in model fit, which may indicate that the predictive capabilities of initial density and island are overlapping.


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: PERFORMANCE IN A NOVEL ENVIRONMENT SUBJECT TO GHOST COMPETITION
Review round: 2
Reviewer: 1

Output:
Basic reporting: I reviewed the first version of this manuscript. I continue to think that the idea of a ghost competitor affecting evolution is a really cool idea that can be tested with the data available here. I concur with the authors that they have demonstrated that the density of T. ludeni affects local adaptation of T. urticae. They have demonstrated that ghost species can alter evolution.

However, I really struggled with this manuscript for days to decide whether I agreed with the authors or not. Parts of the manuscript are really difficult to understand, particularly the Methods section. I would not consider this second version a major revision. Even though I was familiar with the story, it took me even longer to digest this manuscript than the first time. Many of the previous reviewers' comments were not incorporated, which would have greatly improved the clarity of the manuscript. I do not believe that this manuscript is yet ready for publication, as the really cool story they have to tell will be obscured by writing that is difficult to understand.
Experimental design: The experimental design is a fortunate accident, as they ended up able to test a question about ghost species that they had not intended to test. Nevertheless, the experimental design is useful for testing this question.
However, the description of the experimental design is quite poor. The new supplemental figure helps to a large degree. This should be moved into the main text to make the design easier for the reader to digest. I've read through the Methods several times and I could not find any mention of the Control treatment, where each species was continued to be raised on beans. This Control treatment is critical to interpreting the Results, but is not mentioned until then. How many replicates are there of the control treatment? How were they maintained? Were they treated the same as the experimental cucumber treatments?
Validity of the findings: Once I understood the findings, I agree with the authors. It just took me a VERY long time to interpret their design and results in order to determine that I agreed with them.
Additional comments: Additional comments:
-Fig. 1A would be easier to comprehend if the means and errors for each day were presented, rather than every data point. There are so many data points in the figure, that it makes it difficult to observe a pattern (some are even inside the legend). Also, each dot appears to have a light-colored box around it? This figure will also be impossible for the ~5% of the population who are color-blind to interpret. Means with connecting lines would fix this problem.
-The x-axis on Fig. 2 is quite strange. If the x-axis is meant to be the density of competitors, then the light green treatment (no competitors) should be on the left end of the axis, because there were 0 competitors.  The yellow plot does not belong on this axis, as it is an entirely different control treatment in which competitor density was not manipulated. So that treatment cannot have a value on the x-axis.
-I do not see a lot of value in Fig. 3, and if it is to be included, should be in the supplemental material. I believe the intent is to show that drift is not important and that all replicates showed a similar result, but I believe that same information is already presented in Fig. 2 in the form of the error bars.
-Introduction, lines 30-33. I don't see how these two topics are related to this manuscript.
-Introduction, lines 36-37. I would argue that it is not generally expected that conspecific competition will have a bigger effect on evolution than heterospecific competition. I'm also puzzled at this focus on conspecific competition, which is not the subject of this manuscript.
-Most of the introduction is focused on indirect effects that competitors may have (altering the environment or genetic variation, etc.), but what about the simpler direct effects of competitors imposing selection?
-Methods, line 102. It would be worth commenting in the Discussion on why evolution was able to occur so quickly in this experiment (~25 generations), given what seems like extraordinarily low genetic variation in T. urdicae. My understanding is that the culture was started with two females, maintained through inbreeding and kept at low densities in culture for 15 years. I would expect these to be effectively be clones at this point and homozygotes at most loci. Does the genetic variation come from a high mutation rate in this species? Is there a reason to think genetic variation was maintained over the course of this 15 years?
-Methods, line 132: I would not refer to these replicates as "islands", because they are not islands. Each "replicate" is made of three plants, with presumably some dispersal among plants, so if anything, it's a metapopulation, rather than an island. But then habitat/plants are constantly being removed (along with the individuals on that plant), so there is constant removal from the "island", that is then replaced by new habitat.
-Line 324 and elsewhere. I assume that "original" means the control treatments that were grown on bean. One could also interpret this as the cucumber treatment before being transferred to the fecundity assay. Deciding what terminology to use for the which treatments would be useful and more clear if the control treatment were described in the Methods.


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: PERFORMANCE IN A NOVEL ENVIRONMENT SUBJECT TO GHOST COMPETITION
Review round: 2
Reviewer: 2

Output:
Basic reporting: I feel that the authors' basic reporting is good. The manuscript is well-written and with the improvements made after review, it is even better in this regard.
Experimental design: The authors did not address my comment in regards to experimental design, which was my main criticism of the paper. They did a good job of addressing my minor comments, but not this. Therefore, I do not believe that this manuscript should be published in its current form. They simply disagreed without providing a sufficient justification for their disagreement.
Validity of the findings: No additional comment.
Additional comments: I still do not think that it is valid to claim that this work tests ghost competition, because it was not what the experiment was originally designed to test. The hypothesis should be formed a priori and tested, but that is not what is done with this work. Here the authors have formed their hypothesis a posteriori, and I do not think that is valid.


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: PERFORMANCE IN A NOVEL ENVIRONMENT SUBJECT TO GHOST COMPETITION
Review round: 2
Reviewer: 3

Output:
Basic reporting: Some of the new material feels a little bit roughly worded, but overall the paper is clear. References appear to be good, with one minor exception: the authors have added Chesson 2000 as their citation for the role of tradeoffs in species coexistence. While this paper does talk about it, the idea was in the literature since at least the 1970s.

The authors have done some restructuring in response to reviews, which I feel substantially improve the flow of the paper. Figures and tables are professional, and the raw data is shared. The results of this paper are self-contained.

While I think figure 3 may be helpful in data exploration and analysis decisions, I don’t believe it provides information that is important to understanding this paper. I would suggest that it be moved to supplements and the schematic be moved to the main text (I found the schematic very helpful). However, this is up to the authors. I will note that the figure caption references black dots and lines in this figure, which were not visible in my version of the manuscript.
Experimental design: The experiment was well designed, and the new structure and schematic help readers to understand an inherently complicated design. Methods appear to be rigorous, and are described sufficiently to replicate.
Validity of the findings: The authors have carried out a series of analyses to uncover demographic and evolutionary effects of “ghost competitors”. In response to reviews, they have clarified several of their statistical methods, and their approaches are largely statistically sound. With a few exceptions, they have satisfied me with their changes or responses. There are several approaches that are problematic, however.

First, I understand the author’s desire to allow for nonlinearity of time by fitting their 5 census times as a categorical variable instead of continuous one. To the extent that they are working with a maximal model and have sufficient data, this is understandable. However, comparing their model fit procedure for time as a factor vs time as a linear term, AIC strongly supports using time as a linear term. To the extent that they are using model-fitting to support/refute hypotheses of the effect of time, it is unwise to use a poor-fitting metric of time and then discard it when it does not fit well. Given the structure of the maximal model (… time + time*density1 + time*density2…), linear time adds 3 parameters to the maximal model, while time as a factor adds 12, which is likely the cause of the difference in AIC. When I test the authors’ model selection using linear time, the best-fitting model for models B1 and B3 include time. If the authors found that nonlinear relationships with time were important, I would be satisfied, but when the data does not support nonlinearity, it is not satisfying to then disregard simpler interpretations of time.

That said, the authors should not use “presence/absence in best-fitting model” as a metric for whether a term matters, which they do on line 318. There are at least two general issues with this: in the case where several covariates are fairly correlated, if only one is present in the final model, that does not demonstrate that the other is not important (since the first is potentially a proxy for the second). The other issue, which is very relevant here, is that “best-fitting” is different from “only reasonable model”. Models within 2 AIC of one another are generally considered statistically indistinguishable, and in some cases there are models including time that are within 2 AIC of the best fitting model. Looking at the Chisq tests of the maximal model (Table 1), we see that time is marginally significant in predicting fecundity on beans. This is very different from time not mattering. In general, the effect (or lack thereof) of a predictor should be evaluated with hypothesis testing, not model selection.

If time is not a useful predictor of adaptation, do the authors think any evolution happened before the first time point? They might speculate that there was an initial, rapid extinction of certain lineages with or without competitors, and this drove fecundity differences.

I felt that the decision to measure demography with fitted carrying capacity/ stable population size (e.g. the “plateau”) was a good solution to measuring population sizes. However, the plateau is referred to in the paper without enough explanation (first referenced line 263). I think this deserves at least a 1-2 sentence explanation. I think it’s fair to determine the cutoff with visual inspection, but a segmented regression (sometimes called broken stick regression) could be used to allow the data to inform the author’s decision of the cutoff for the plateau. If it were me, I would consider using the segmented package in R to find the best breakpoint for the three relevant categories (T. urticae with and without competition, T. ludeni without competition), and ensuring the author’s cutoff for the plateau was after the various estimated break points. Even simply stating that 200 was chosen as a cutoff by visual inspection, and referencing how this compares to the segmented approach would help validate that specific cutoff.

The authors do a nice job of distinguishing between changes in fecundity (which imply evolutionary effects of competitors) and plateau population size. They attribute plateau population size to ecological processes. While this is a reasonable interpretation, another is that plateau population size is a function of carrying capacity, which could be a function of organismal traits. Under this paradigm we would interpret that authors results as selection for growth rate but not carrying capacity in response to ghosts of competitors. I believe there are some standing hypotheses about tradeoffs between resource acquisition and resource efficiency that the authors could then tie their findings into. I think adding some framing in this direction could be interesting, but the decision to do so is in the authors’ hands. However, I think it would be wise to mention the possibility that plateau population size could be the consequence of adaptation, rather than just assuming it is only the consequence of ecological processes.
Additional comments: Overall I think this is a really interesting study. I have a number of suggestions for word changes or potential ambiguities to avoid, but in general I like this manuscript. Please consider the following as “someone was flagging things that might be worth changing” rather than “these things must be done this way or the manuscript will be rejected”.

•	I would consider modifying the start of the paragraph starting line 64. The initial sentence implies an assumption that the inferior competitor will always go extinct, but there are a number of mechanisms that allow competitively inferior species to coexist with superior competitors (unless competitively inferior is defined solely as “unable to coexist”). Since this isn’t the focus of this paper or the important part of this paragraph, I think it would be easier to talk about how even when a species is predicted to go extinct, it can still co-occur for many generations
•	Line 130-146: I think it would be helpful to actually start by outlining that the authors made “novel host islands” with sticky tape etc (e.g. line 148), and started by placing 2 plants adjacent to each other (e.g. 131)
•	Line 175 “approximately” instead of “about”. While I did not track them all, there are other cases where unnecessarily informal language was used. Consider making a pass of edits looking for these sort of cases.
•	195: missing an “a” between “as” and “proxy”
•	200-202: How do bean discs prevent evolution?
•	Line 206: I think “specifically” is more appropriate than “especially”
•	Lines 248 etc are pretty clearly a consequence of overfitting with the full model: the authors could list that rather than the more generic “convergence problems”.
•	The paragraph line 309 is a little bit complicated. The authors repeatedly talk about populations being more or less fecund; while this may be acceptable shorthand, it feels ambiguous whether this is an ecological or evolutionary measurement. What the authors measured was the low-density fecundity of individuals sampled from these populations (well, really, their grandchildren, if I read the methods correctly). And the actual measurements they made were far more interesting than observed births in a census of the population/population size, which is what “population fecundity” might imply. It might be useful to think about if there is a clear way to convey that succinctly. If not, the present approach feels workable.
•	Line 356/357 – I’m not sure that it’s correct or necessary to mention where the extra energy is allocated. Simply stating that T. urticae might have higher resource efficiency is both simpler and more true (larger population size could be a consequence of extended lifespan, for example, or reduced resource requirement per individual).
•	Line 368: The “we speculate” sentence and the following sentence can be combined by selecting that the competitive pressure letd to the evolution of increased fecundity
•	Something that struck me only late in this paper is that the authors measurement of fecundity does a great job of isolating the effect of mite trait evolution from any kind of direct or indirect effect mites have on their host plant. This is a really cool consequence of their experimental design, and it’s something they could emphasis in the methods (unless I missed it, in which case perhaps it would benefit from clearer emphasis).
•	Lines 374-375: appears to have some redundant references to the novel host plant
•	Paragraph on line 374 confused me. The presence/absence of differences in fecundity was unclear, and seemed to contradict the findings earlier in the paper. I would suggest spending a bit of time clarifying this paragraph
•	Line 395: “performance” can mean many things. Did the authors mean mean fecundity? Or final densities?
•	Line 399-401: If ecological specialization in this context is niche differentiation, I would expect performance differences would show up in the context of competition, rather than improved performance on their own. This is likely to be most readers’ intuition, so if this is a different dynamic, clarification is needed.
•	Line 425 “in creating” rather than “to create”?
•	Figure 1A: data overlap with the legend make it hard to read the legend. T. urticae  (no comp) is green, not pink, but that is somewhat confusing to determine at first glance.
•	Figure 1A: caption talks about grey zone for 95% CI, but not visible to me.
•	Figure 1B: is this pooled across all time points? Worth mentioning in caption.
•	Caption for fig 2 talks about a significant interaction between density of T. ludeni and fecundity of T. urticae. I think the authors mean significant relationship? Fecundity is the response variable, so interaction is not the right word.
•	Table 1, bottom section: the title says without interspecific competitor, but one of the treatments is with vs without competitors. I found this confusing
•	In general, the formulas in table 1 are hard to read. Consider putting them on their own line, and perhaps using further abbreviations, labeled in the table caption, so that each formula fits on a single line. I would also appreciate seeing the df of the maximal model
•	Table 3 gives us the most relevant information of all the tables – how did parameters differ? I really appreciated having this, but given the number of models run, it would probably be useful to have reminds of the time periods being compared, and the units of the estimates
•	Similarly, table 4 has fecundity listed in some sections and not others
•	The lines in the R code that read in the data files are missing underscores (I suspect the underscores of the were added by the data repository)
•	The selection of error distribution in the code is somewhat dissatisfying. Using the visual tests of goodness of fit for distributions (e.g. "A fitted distribution should be evaluated using graphical methods (goodness-of-fit graphs automatically provided in our package by plotting the result of the fit (output of fitdist() or fitdistcens() and the complementary graphs that help to compare different fits - see ?graphcomp)." ~ fitdistrplus vignette) show the normal distribution as the clear best option for a number of the models. If the authors have decided a priori that they are uncomfortable using the normal distribution because they have non-negative count data (which is a reasonable feeling), they should exclude that as an option in their model fit code rather than include it and then ignore it.


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

Input:
Title: POST-TRANSCRIPTIONAL REGULATION OF SEVERAL BIOLOGICAL PROCESSES INVOLVED IN LATEX PRODUCTION IN HEVEA BRASILIENSIS
Review round: 1
Reviewer: 1

Output:
Basic reporting: Minor concerns

Abstract:  the authors should cite the importance of small RNAs during viral infections  (lines 29-31)

Abstract: Authors should avoid contractions in the abstract before define them, such as MIR and ta-siRNAs (line 36)

Line 146: Table 1 is linked to a publication (Zhang et al., 2019) which is not present in the reference list. Since there is not publication accessible, authors could explain why use bowtie instead bowtie2 to the alignment of paired-end long reads?

In Figure 11, authors should highlight Hevea proteins to improve the understanding. In the case of the other organism proteins, they should be named according to its gene symbol no only accession code.

Main concerns

One of the main characteristics of miRNAs is the base preference. Most of miRNA show 5’ U base preference. The authors should show base preference per size for small RNAs derived from miRNAs as a positive control

Texts within images in some main figures (1,2,5, 6, 8). They need to be improved to allow better interpretation of the images.

The authors produced a large number of images, which I believe the number is exaggerated in the case of main figures, but do not produce an image demonstrating Biological Processes of cleaved targets?  Why do not perform GO enrichment analysis?

Figures 9 and 10 are not legible nor understandable. I suggest to improve them, enlarge in supplemental figures or remove.
Experimental design: no comment
Validity of the findings: - I believe the authors showed a large amount of data to prove its hypothesis. However, some basic analysis should be performed in order to corroborate their findings:

- Describe about the identification of highly conserved miRNAs (such as let-7 and others)
- Base preference od miRNA-derived small RNAs
- Correlation between miRNA expression,  transcript expression and degradome, demonstrating the complete mechanism of regulation (since we expects high expression of miRNAs leading to decreasing in the expression of mRNAs due its degradation assessed by degradome)
Additional comments: In this manuscript,  Leclercq & Wu et al took advantage of RNA deep sequencing to assess the transcriptional profile of Hevea brasiliensis and its regulation strategies. The authors made an incredible effort to integrate a large number of datasets. Although I believe the manuscript is well written and full of data,  the manuscript in very dense and needs simplification and clarification in some parts. Therefore,
there are some points should be addressed in order to improve the reading and understanding of the findings.


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: POST-TRANSCRIPTIONAL REGULATION OF SEVERAL BIOLOGICAL PROCESSES INVOLVED IN LATEX PRODUCTION IN HEVEA BRASILIENSIS
Review round: 1
Reviewer: 2

Output:
Basic reporting: The authors present a detailed analysis of small RNA populations, degradome, and RNA expression in Hevea to better understand the potential changes in trees with Tapping Panel Dryness (TPD).  Analyses further define the molecular changes and functional networks in TPD affected trees.  In addition, data is provided for multiple Hevea tissues types.  The authors find that the increase previously reported for 21-nt siRNAs is not due to miRNA increase, but rather siRNAs.

While not clearly stated, it appears that a driving hypothesis behind this research was investigation of post transcriptional regulation associated with Tapping Panel Dryness (TPD).  Previous research has shown a change in small RNA size (lines 81-82).  Unfortunately, this comes off as a side bar in the introduction and results.  The research question being addressed needs more clarification and addressed in these sections.  Otherwise this manuscript comes off as more observational. It is an interesting finding that 21-nt siRNAs increase in TPD.  Unfortunately, the focus of the manuscript is on miRNAs and impacted pathways, rather than genes that might be impacted by siRNAs in the disease response.  This would be an interesting analysis to include.

The figures and tables presented are challenging to interpret and make the manuscript inaccessible to general audiences.  The authors should revise the figures that can be interpreted by audiences not familiar with the complex statistics behind the analysis.  For example, I could not follow the analysis of cleaved targets described (lines 193-201), and relate this to the results presented (Figures 6, 8). Tables 1, 2, 3, 4, 7, 9 do not help explain the results found.  They are simply descriptive statistics.  Figures 9 and 10 are illegible; I cannot tell what the networks described here would be.

Please include a description of the data provided in all supplemental materials.

Overall, this manuscript could be greatly improved through focus on a specific question and in depth analysis.  The figures need to be redone to help the reader follow the conclusions made by the authors.
Experimental design: The methods used are appropriate and follow rigorous statistical analyses.
Validity of the findings: I don’t see a significant difference in small RNA populations in Figure 5, as previously reported and discussed by the authors (Line 283). This requires explanation why there might be a difference between the reports.
I find limited value in the analysis of post transcriptional gene families in Hevea.  This does not add to the manuscript as written.  The analysis could be in improved with a broader phylogenetic analysis and comparative genetics with other species.  The manuscript could be improved by limiting or removing this component and focusing on the gene regulation in Hevea.
The authors present a case that canonical miRNA and ta-siRNA genes have evolved to target new gene families; this is quite a novel discovery as miRNA:RNA pairings have been shown to be highly conserved throughout plant evolution (starting line 327).  A deeper analysis, showing lack of sequence homology with canonical miRNA:RNA pairs is required to make this strong conclusion.  Very strong conclusions are made (350-354) that need to be supported with sequence alignments and clear demonstration of cleavage. The authors are suggested to review mIRNA literature for published ways to show this information.
The link between the ethephon treatment and TPD plants was not clear to me.  These appear to be disparate experiments pulled together in one paper.  The authors should tie these analyses together, if they should be (405-423).
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: ECMPRIDE: PREDICTION OF HUMAN EXTRACELLULAR MATRIX PROTEINS BASED ON THE IDEAL DATASET USING HYBRID FEATURES WITH DOMAIN EVIDENCE
Review round: 1
Reviewer: 1

Output:
Basic reporting: The manuscript by Liu et al describes the development of a novel tool for the prediction of extracellular matrix (ECM) proteins to be potentially used as a reference resource for ECM protein identification. Regarding basic features of the manuscript, it is written in a correct, clear way and conforms the standards of courtesy and expression. Moreover, the use of literature references is adequate and, in general terms, it is well structured.
Experimental design: In general, the experimental design is correct. The development of the theoretical tool is well explained and, according to the information provided by authors, is superior to previous tools (Matrisome).
Validity of the findings: To test the validity of the tool to predict ECM proteins, authors applied their algorithm to all human entries in the SwissProt database and compared the results with the most widely used dataset, the human Matrisome. Based on the information provided by the authors, ECMPride detected 706 novel ECM components (not found with Matrisome), while most of the ECM components detected by this tool were also recognized by ECMPride. While the new approach constitutes a remarkable improvement in the detection capacity, there are concerns that should be taken into consideration when throwing conclusions about the performance of ECMPride. To this aim, authors only proposed several candidates and analyzed their expression by immunofluorescence in different tissues, indicating that the tissue distribution is compatible with the localization in the extracellular matrix compartment. This is in fact interesting but, to my opinion, fails short in the attempt to validate their tool.
Theoretically, an ECM component is defined as a protein that is secreted by cells into the extracellular medium and somehow incorporated to the insoluble material that surrounds the cell, together with the cell machinery required to build and remodel this insoluble material. This sophisticated definition can in no way be reduced to a single experiment showing the tissue localization of a particular protein component. In fact, being an ECM component is a dynamic definition that requires a long way validation from the very early identification as a potential candidate to the confirmation by a variety of experimental evidences (analysis of its biosynthesis, secretion, binding to known components, modification, expression as a recombinant protein and many, many more). Software tools such as the one developed by Liu et al are nevertheless tremendously useful in the initial step of identification of potential components, but the manuscript, in its present form, cannot establish this rigorous analysis to confirm that such or such component is in fact ECM. I would definitely remove the IF analysis and concentrate on what I find more useful at using their tool.
For me, the most important point is to perform a more profound comparison with the previous gold-standard approach to identify ECM components, the Matrisome. In other words, I think it is more relevant to discuss why about 700 potential ECM components were detected by ECMPride that were not with Matrisome. Whether they have something in common, hints about their pathophysiological relevance, etc. And the other way around, those components that were detected by Matrisome and not by ECMPride. Why has this occurred? What is it based on? Are they in fact ECM components?
Additional comments: Already discussed in the previous areas above.