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: DISTURBANCE HAS LASTING EFFECTS ON FUNCTIONAL TRAITS AND DIVERSITY OF GRASSLAND PLANT COMMUNITIES
Review round: 3
Reviewer: 2

Output:
Basic reporting: I recall commenting on this before and it still stands – disturbance is used way too often and way too loosely throughout the manuscript.  It’s a good study, but use of disturbance and variations on this word in this way hides the true nature of the experimental design and results in an overreach.  In many places it would be much more accurate to use the “gap” terminology – i.e. L116 – e.g. change to species colonizing gaps. Additionally, I find the manuscript overall lacking in essential explanations regarding how these gap areas were revegetated – was this colonization by seed, vegetative spread from edges, or even recruitment from plants that weren’t effectively terminated (which could very well happened).
Some specific comments:
L 53 – Over reach on claim that all disturbances would result in this same effect.  This is one type of a disturbance that effectively assesses functional trends in early succession.  The language needs to be changed
L58 – such as insert as
L84 -85 – Recovery after mortality would be better here
Study design – It would be good to explicitly articulate that it’s a split plot design
L147 – Give the manufacturer info and application concentrations for the Roundup
L151 – add “without a soil disturbance” to the extreme event clause
L151-153 – So how did you handle the seedling that did emerge during the termination window?  I’m assuming that any newly germinated individuals were also terminated – but that could be explicitly stated here – if so, it did affect the seed bank because recruits were terminated.  Theres a window of potential recruitment here that needs to be addressed in how it was handled and what effect it would have on the study outcomes
L156 – The word regenerated is used here – that means that there was growth from established plants, which it says above that they were all terminated.  Make it clear that this was growth that resulted from new seedling recruitment – if not and the treatment didn’t kill all of the plants or that there’s evidence of tillering from outside of the plots, that needs to be clear. Great line where calling them “gap” plots would make a whole lot more sense
Experimental design: See comments above - especially re: explicitly stating that it was a split-plot design
Validity of the findings: see comments above
Additional comments: see comments above


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

Input:
Title: A LONGITUDINAL STUDY OF RISK FACTORS ASSOCIATED WITH WHITE SPOT DISEASE OCCURRENCE IN MARINE SHRIMP FARMING IN RAYONG, THAILAND
Review round: 1
Reviewer: 1

Output:
Basic reporting: Abstract: line 27, October 2007. Would it be 2017?

For introduction:
-	I suggest that the authors should provide more crucial information about WSD situation such as severity, the impact to economy and the decision to study in Rayong province. The reader will better understand how important of this work.
-	Since there were a few reports on the risk factor of WSD in Thailand carried out by different statistical analysis, so, I suggest that the authors should give the detail of pros and cons of your method compared to others.
Experimental design: Questionnaire part: the authors mention that you designed the questionnaire based on the research from Yaemkasem et al., 2017 and Piamsomboon, Inchaisriand & Wongtavatchai, 2015. I suggest that you should separately describe what the factors are from those previous works and what the new additional factors are in this study.

Shrimp sample collection and WSD status part: I suggest that the authors should briefly explain more about the organ for detection, DNA extraction step, PCR interpretation and the PCR results of the testing are from individual or pooled sample of an investigation, please specify.
Validity of the findings: -	As the result of statistical analysis, the inclement weather was indicated as one of the risk factors of WSD. So, to figure it out, the authors should specify or give an example how the inclement weather be in those actual situations.
-	Line 175-181: Once the authors discussed about the owner operation which is not influence to WSD in this study but inconsistent with the previous report. What is the different between previous study and yours? The study area? The statistical method? If it is because of the statistical method, which one is more accurate? Please discuss.
-	The results need more figures about WSD status such as the shrimp showing WSD clinical signs and PCR positive result.
-	In a nutshell, do you think that the risk factors obtained from Rayong model would also influence WSD in another shrimp cultured area in Thailand? Please discuss.
Additional comments: It is a good scientific study on the multiple risk factors of WSD occurrence. Also, it has a very well conducted with an approval of animal ethics. However, to make it more complete, some minor details need to be improved as I mentioned above.


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

Input:
Title: A LONGITUDINAL STUDY OF RISK FACTORS ASSOCIATED WITH WHITE SPOT DISEASE OCCURRENCE IN MARINE SHRIMP FARMING IN RAYONG, THAILAND
Review round: 1
Reviewer: 2

Output:
Basic reporting: The study reported is an interesting one and the longitudinal study has attempted to identify potential  risk factors related to one of the most significant diseases, white spot disease caused by white spot syndrome virus (WSSV), affecting farmed shrimp. The study identified 17 statistically significant risk factors associated with WSSV. The information generated will be helpful in formulating management measures against WSSV. Following are the specific comments:

In the first part of the manuscript (Methods) as well as in Line No. 27 – The period of survey is mentioned as October 2007 – September 2019.  However, this a two-year survey and it needs to be corrected as October 2017 - September 2019

Title: Can it be modified as A longitudinal study of risk factors associated with white spot disease occurrence in marine shrimp farming in Rayong, Thailand ?

Introduction:  It has covered brief reviews. The statement of problem which highlights the gaps in past research studies has not been defined well. The researchers have mentioned that only few studies have applied analytical techniques to understand factors that may vary over time. It can be modified and rewritten with more empirical facts.

Materials and Methods:

Suitable research design has been applied in the present study.

The collection tool should be corrected as Interview Schedule instead of Questionnaire, as interview schedule is filled by researchers in face-to-face interaction whereas questionnaire is filled by the respondents.

The researchers have followed the standard method for developing Interview Schedule.

The data were collected only twice in two years. How many crop cycles have been covered under the study? A longitudinal study allows researchers to look at changes over time. Therefore, study must include the data on WSD status in consecutive crop cycles in the same farms.

Results:
The results are presented concisely.

If the 17 possible risk factors found in the study can be mentioned with their alpha level associated with WSD status, it would be useful to other researchers to conduct further research in the same line.

The study focussed only on farm characteristics, farm practices, and biosecurity measures in relation to the occurrence of white spot disease. However, do you think farm owners’/farm managers’ attributes such as knowledge, skill, experience,  training status, innovativeness, etc. will have any bearing on the occurrence of  white spot disease.

Discussion:
The results of the present study are well discussed in the light of past study findings.

Conclusion:
It is mentioned that “The findings of this study will help farmers and relevant authorities focus on possible risk factors during the shrimp cultivation period. In addition, it can be advantageous in limiting WSD occurrence in Rayong” . The authors may state whether these risk factors will be limited only to a particular location or it will be applicable to other shrimp-growing areas as well. The conclusion may be modified.
Experimental design: The study reported is an interesting one and the longitudinal study has attempted to identify potential  risk factors related to one of the most significant diseases, white spot disease caused by white spot syndrome virus (WSSV), affecting farmed shrimp. The study identified 17 statistically significant risk factors associated with WSSV. The information generated will be helpful in formulating management measures against WSSV. Following are the specific comments:

In the first part of the manuscript (Methods) as well as in Line No. 27 – The period of survey is mentioned as October 2007 – September 2019.  However, this a two-year survey and it needs to be corrected as October 2017 - September 2019

Title: Can it be modified as A longitudinal study of risk factors associated with white spot disease occurrence in marine shrimp farming in Rayong, Thailand ?

Introduction:  It has covered brief reviews. The statement of problem which highlights the gaps in past research studies has not been defined well. The researchers have mentioned that only few studies have applied analytical techniques to understand factors that may vary over time. It can be modified and rewritten with more empirical facts.

Materials and Methods:

Suitable research design has been applied in the present study.

The collection tool should be corrected as Interview Schedule instead of Questionnaire, as interview schedule is filled by researchers in face-to-face interaction whereas questionnaire is filled by the respondents.

The researchers have followed the standard method for developing Interview Schedule.

The data were collected only twice in two years. How many crop cycles have been covered under the study? A longitudinal study allows researchers to look at changes over time. Therefore, study must include the data on WSD status in consecutive crop cycles in the same farms.

Results:
The results are presented concisely.

If the 17 possible risk factors found in the study can be mentioned with their alpha level associated with WSD status, it would be useful to other researchers to conduct further research in the same line.

The study focussed only on farm characteristics, farm practices, and biosecurity measures in relation to the occurrence of white spot disease. However, do you think farm owners’/farm managers’ attributes such as knowledge, skill, experience,  training status, innovativeness, etc. will have any bearing on the occurrence of  white spot disease.

Discussion:
The results of the present study are well discussed in the light of past study findings.

Conclusion:
It is mentioned that “The findings of this study will help farmers and relevant authorities focus on possible risk factors during the shrimp cultivation period. In addition, it can be advantageous in limiting WSD occurrence in Rayong” . The authors may state whether these risk factors will be limited only to a particular location or it will be applicable to other shrimp-growing areas as well. The conclusion may be modified.
Validity of the findings: The study reported is an interesting one and the longitudinal study has attempted to identify potential  risk factors related to one of the most significant diseases, white spot disease caused by white spot syndrome virus (WSSV), affecting farmed shrimp. The study identified 17 statistically significant risk factors associated with WSSV. The information generated will be helpful in formulating management measures against WSSV. Following are the specific comments:

In the first part of the manuscript (Methods) as well as in Line No. 27 – The period of survey is mentioned as October 2007 – September 2019.  However, this a two-year survey and it needs to be corrected as October 2017 - September 2019

Title: Can it be modified as A longitudinal study of risk factors associated with white spot disease occurrence in marine shrimp farming in Rayong, Thailand ?

Introduction:  It has covered brief reviews. The statement of problem which highlights the gaps in past research studies has not been defined well. The researchers have mentioned that only few studies have applied analytical techniques to understand factors that may vary over time. It can be modified and rewritten with more empirical facts.

Materials and Methods:

Suitable research design has been applied in the present study.

The collection tool should be corrected as Interview Schedule instead of Questionnaire, as interview schedule is filled by researchers in face-to-face interaction whereas questionnaire is filled by the respondents.

The researchers have followed the standard method for developing Interview Schedule.

The data were collected only twice in two years. How many crop cycles have been covered under the study? A longitudinal study allows researchers to look at changes over time. Therefore, study must include the data on WSD status in consecutive crop cycles in the same farms.

Results:
The results are presented concisely.

If the 17 possible risk factors found in the study can be mentioned with their alpha level associated with WSD status, it would be useful to other researchers to conduct further research in the same line.

The study focussed only on farm characteristics, farm practices, and biosecurity measures in relation to the occurrence of white spot disease. However, do you think farm owners’/farm managers’ attributes such as knowledge, skill, experience,  training status, innovativeness, etc. will have any bearing on the occurrence of  white spot disease.

Discussion:
The results of the present study are well discussed in the light of past study findings.

Conclusion:
It is mentioned that “The findings of this study will help farmers and relevant authorities focus on possible risk factors during the shrimp cultivation period. In addition, it can be advantageous in limiting WSD occurrence in Rayong” . The authors may state whether these risk factors will be limited only to a particular location or it will be applicable to other shrimp-growing areas as well. The conclusion may be modified.
Additional comments: No additional comments


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

Input:
Title: A LONGITUDINAL STUDY OF RISK FACTORS ASSOCIATED WITH WHITE SPOT DISEASE OCCURRENCE IN MARINE SHRIMP FARMING IN RAYONG, THAILAND
Review round: 2
Reviewer: 1

Output:
Basic reporting: no comment
Experimental design: no comment
Validity of the findings: no comment
Additional comments: I appreciated that the author and team have revised manuscript from all my comment very well. I have no doubt on any parts of the manuscript.


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

Input:
Title: A LONGITUDINAL STUDY OF RISK FACTORS ASSOCIATED WITH WHITE SPOT DISEASE OCCURRENCE IN MARINE SHRIMP FARMING IN RAYONG, THAILAND
Review round: 2
Reviewer: 2

Output:
Basic reporting: The manuscript is presented in an acceptable standard.
Experimental design: Research question well defined and relevant.
Validity of the findings: Findings are valid and has practical relevance.
Additional comments: The authors have addressed all the comments made by the reviewer and the manuscript has been improved. Therefore, the manuscript is recommended for acceptance.


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: ACUTE KIDNEY INJURY-ATTRIBUTABLE MORTALITY IN CRITICALLY ILL PATIENTS WITH SEPSIS
Review round: 1
Reviewer: 1

Output:
Basic reporting: The main topic and aim of the authors are clearly explained. The discussion highlights the point of interest of the authors and made meaningful comparisons with current literature.
No major concerns regarding English used, some minor mistakes that can be easily corrected.
Most of the references are meaningful and used properly in the different parts of the manuscript. A couple of reference need to be updated/corrected (line 72 and lines 77-78).
No major concerns regarding the structure of the article and the results shown are relevant to the hypotheses.
Figures and tables are good and clearly highlights the results of the authors. Particularly good is figure 2 to summarize the results.
Raw data regarding the Wenzhou cohort are shared correctly with an excel file available for analysis. Not data regarding. No data regarding the MIMIC IV are shared, to be clarified if it is because too large to be shared with a sample datasheet or for other restrictions.
Experimental design: Research question is well defined, relevant and meaningful. Probably a little expansion of current/previous evidence regarding the association between AKI and mortality should be mentioned already in the introduction. What is actually new in this paper is not the discovery of how AKI increased mortality in critically ill patients with sepsis, but to have clearly measured this association with excess of attributable mortality (and the authors clearly highlight this in lines 214-215 and  235-237 at the end of the discussion).
The methods section and supplemental material explain most of the methodology and statistical analysis. However, some aspect needs to be clarified:
•	KDIGO criteria using serum creatine have two time-windows for assessment of AKI: the 48-hour window (increase of serum creatinine>0.3 mg/dL) and the 7-day window (increase of serum creatinine >1.5 time baseline).  In the Supplemental Material you mentioned only the 7-day time frame but later in page 3 of the Supplement you showed all the KDIGO criteria, as well the 0.3 mg/dl increase criteria (together with the 1.5-1.9 times baseline serum creatinine). Please clarify if you used also the 0.3 mg/dl increase and in which time window.
•	When assessing AKI it is always crucial the definition of "baseline creatinine" since it is what is used to define at the end the presence or not of AKI. This might be tricky sometimes particularly in retrospective studies without predetermined protocolization of serum creatinine/AKI assessment. In the literature different ways are proposed: using the last previous known values of serum creatinine before event index, the mean/median of serum creatinine values in the previous year, admission creatinine at enrollment, back-calculation using MDRD formula from estimated eGFR of 60 ml/min, etc. This should be specified, if there is not space in the methods, in the supplement.
•	I will suggest reviewing the paragraph “Primary outcome and additional variables” in the methods section to improve clarity and possibly to divide it in two sections (e.g.: “patients” and “outcomes”).
Validity of the findings: The authors provided important clinical data and they correctly highlighted one of the most important implication of their findings at the end of discussion: “Our findings would guide the evaluation of the plausible effect size for future clinical trials regarding the prevention or treatment of AKI”. I agree with this statement, and I found particularly important the comparison with previous evidence regarding other ICU disease.
The statistical approach used to try to adjust for possible confounders is worth of merit and robust.
The results and the discussion may need just a few minor edits to avoid useless repetition that could allow the authors to have more space to correctly highlight the implications of their findings. I suggest avoiding as much as possible repetition of results clearly and already shown in the tables (e.g.: lines 129-132, 156-159, 204-207, 233-235).
Limitations are clearly stated. If some of the issues I have raised regarding the definition of AKI and baseline creatinine are not possible to be address for the intrinsic nature of this retrospective analysis, they should be stated here.
Conclusions are well stated and limited to supporting results.
Additional comments: I have highlighted in the pdf file of the manuscript  some of the issues reported above together with a comments. Please check them.
Regarding the supplement online material:
-second footnote Table S2 and S3: Why not gender? It is not gender is not specified in Table S1 as not considered for Wenzhoud cohort. Or is it just missing in the footnote?
-description of table s4: why EARLY and VALID cohort are mentioned here? Is this a misplacement?
-check references 2, 3 and 4 according to what will be changed/modified in the main text.


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: ACUTE KIDNEY INJURY-ATTRIBUTABLE MORTALITY IN CRITICALLY ILL PATIENTS WITH SEPSIS
Review round: 1
Reviewer: 2

Output:
Basic reporting: Well done
Experimental design: Well done
Validity of the findings: Well done
Additional comments: Well done


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: ACUTE KIDNEY INJURY-ATTRIBUTABLE MORTALITY IN CRITICALLY ILL PATIENTS WITH SEPSIS
Review round: 1
Reviewer: 3

Output:
Basic reporting: Generally well written in professional English with few concerns herein.

1) Note AKI is spelt KAI in line 122.

2) line 283- reference states "and et al" at the end of the author list, whereas all the other reference list all authors.

3) The sentence in line 46 "The excess mortality among patients with AKI, that is, the AKI-related deaths could be avoided without the development of AKI" appears either to be a sentence fragment or a tautology. It is best removed from the manuscript.

4) line 70 "Inclusion criteria for adult patients followed the definition of sepsis-3" is unclear: it appears like a typing error, until I realised it should be "Inclusion criteria for adult patients followed the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)."

5) In line 212, "The AF of mortality from sepsis was 15% compared to ICU-non-sepsis (Shankar-Hari et al. 2018)" doesn't make sense. It should simply state " "In ICU patients, the AF of mortality from sepsis was 15% (Shankar-Hari et al. 2018)".

6) Several times in the manuscript, the abbreviation (ARF) is used instead of AKI, and ARF is never defined. ARF should be deleted.
Experimental design: There are significant methodological issues:

1) It is unclear why the authors chose to present the same analysis performed on two different cohorts (a larger MIMIC-IV cohort, and a much smaller Wenzhou cohort). Why was this done, instead of combining the Wenzhou patients together with the MIMIC-IV patients to make a single cohort (with analyses simply adjusting for country of location?) This would have cut down the extraneous length of the article significantly. Do the authors have a particular hypothesis about the AKI/sepsis relationship in different countries that they are trying to answer?

2) There is too much relegation of important methodological data to the supplementary material. The directed acyclic graph is unnecessary, and its explaining paragraph in the supplementary material is unclear as the graph does not explicitly label the "indirect pathway". It is important for readers of the primary manuscript to understand the variables taken into account in multivariate models without having to be directed to supplementary material. I suggest that the directed acyclic graph and table S1 be removed, all their relevant data be summarised in text and added to the main manuscript, and a summarised version of the "statistical methods" section in the supplementary material added instead to the main text.

Therefore, the phrase "(variables inclusion criteria are described in Supplementary materials)" in line 137 can also be removed.

3) Line 204 states "The AFAKI is the proportion of deaths attributable to AKI in patients with AKI, whereas the population AFAKI is the proportion of all deaths in the sepsis population attributable to AKI." This is slightly different to the previous definitions given in line 104, and therefore line 204 is both confusing and unnecessary.
Validity of the findings: 1) The lines 114 to 121, describing the differences in baseline characteristics between the MIMIC cohort and the Wenzhou cohort, are not backed up by any statistical evidence (e.g. p values) in Table 1. Table 1 only offers p values comparing AKI/non-AKI subgroups within each country's cohort.

2) Line 214 states "Notably, we found that the AF of AKI in patients with sepsis was higher than in other ICU disease states". This is misleading, as it suggests that the current study has included comparator groups of patients that did not have sepsis, which it did not.

3) Similarly lines 208- 211 are written in a confusing  manner, with incongruent use of abbreviations. They should state "In one study of critically ill patients with liver cirrhosis, the AFAKI from mild AKI was 25% and the AFAKI from severe AKI was 51% (du Cheyron et al. 2005), whereas the 90-day AFAKI in ICU patients was 8.6%, and population AFAKI was nearly 20% (Vaara et al. 2014) in another 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: ACUTE KIDNEY INJURY-ATTRIBUTABLE MORTALITY IN CRITICALLY ILL PATIENTS WITH SEPSIS
Review round: 2
Reviewer: 1

Output:
Basic reporting: Most of the points presented in my revision have been addressed and clarified.
Experimental design: no comment
Validity of the findings: no comment
Additional comments: no comment


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

Input:
Title: ACUTE KIDNEY INJURY-ATTRIBUTABLE MORTALITY IN CRITICALLY ILL PATIENTS WITH SEPSIS
Review round: 2
Reviewer: 2

Output:
Basic reporting: acceptable
Experimental design: My previous issues have been answered.
Validity of the findings: My previous issues have been answered.
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: CROP DAMAGE BY VERTEBRATES IN LATIN AMERICA: CURRENT KNOWLEDGE AND POTENTIAL FUTURE MANAGEMENT DIRECTIONS
Review round: 1
Reviewer: 1

Output:
Basic reporting: no comment
Experimental design: I have some doubts as to why authors included only the first 50 records from Google Scholar. This are probably the ones that have been more accessed, but not necessarilly the most recent.

I don´t think I understood what authors want to say in lines 220-223

Why were thesis and gray literature not included in the review?, they can also have relevant data and information.

I do not see the relevance of including if the research papers include the exact coordinate. I consider the authors go through this extensively.
Validity of the findings: The authors mention that relying on the perception of farmers on crop damage can be misleading as their ideas of which species are responsible for damaging crops. I think that the farmers´ day to day experience on examining the damage in their crops provides very important knowledge as to clearly identifying which species are related to the different damages.
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: CROP DAMAGE BY VERTEBRATES IN LATIN AMERICA: CURRENT KNOWLEDGE AND POTENTIAL FUTURE MANAGEMENT DIRECTIONS
Review round: 1
Reviewer: 2

Output:
Basic reporting: The review of the literature was insufficient.
Experimental design: The choice of key terms to the search is biased towards some orders of Mammals. Considering that one of the keywords (Line 66) is “bird damage”, and that several of the references that you cited in the Introduction section are related to birds (such as: Lines 106-107: Canavelli, Swisher & Branch, 2013; Lines 107 and 141: Linz et al., 2015; Lines 144-145: Mitchell & Bruggers, 1985). Please explain why did you not use the term “Bird” in your search? Not including this term (and, for example, considering “Mammal”) may skew the results.
Validity of the findings: The results, discussion and conclusion are conditioned by the strong bias to Mammals (instead of including all Vertebrates).
Additional comments: General comments:

The study is attempts to address the current knowledge crop damage by vertebrates in Latin America through literature review. However, the articles search criteria are biased towards certain Orders of Mammals (please, see particular comment Lines 160-167). So, the list of studies included in the review is incomplete. The results, discussion and conclusion are conditioned by this bias.
At the end, I added a list of some relevant works that were missing from the review.

Particular comments:

- Introduction

Lines 84-90: These sentences refer to “pests” in general. These data correspond mainly to losses due to invertebrate pests, insects particularly. I suggest incorporating, below, background on the losses caused by vertebrates to crops.

Lines 105-116: An important topic that is missing from this paragraph is that lethal control can also generate contamination as a result of the use of poisons as toxic baits to kill vertebrate pest, and this may cause social problems. I suggest that you include that topic.

- Survey methodology

Lines 160-167: The choice of key terms to the search is biased towards some orders of Mammals. Considering that one of the keywords (Line 66) is “bird damage”, and that several of the references that you cited in the Introduction section are related to birds (such as: Lines 106-107: Canavelli, Swisher & Branch, 2013; Lines 107 and 141: Linz et al., 2015; Lines 144-145: Mitchell & Bruggers, 1985). Please explain why did you not use the term “Bird” in your search? Not including this term (and, for example, considering “Mammal”) may skew the results.

Line 175-176: Why is this clarified? According to Line 159 the search in dataset included Google Scholar already. Please, clarify.

Line 176: Was the search and review carried out by one of the authors (Line 158) or by both authors (Line 176)? Please, clarify.

Lines 210-225: Please, see previous comment Lines 160-167. Due to the terms included in the search, the results may be biased towards Mammals, instead of including all Vertebrates.

Lines 240-246: The information in the figure 1 is redundant with the information in the text.

- Results

Line 252 and figure 2: The search was carried out between May 2020 and May 2021 (Line 160). So, the year 2021 cannot be compared with the other years because only five months of the year was analyzed.

- Some examples of missing studies:

Category (1) Crop damage evaluation, if the damage caused to crops by vertebrates in the area was assessed (Lines 178-179).

- Canavelli et al. (2014) Multi-level analysis of bird abundance and damage to crop field. Agriculture, Ecosystems & Environment 197:128-136. DOI: 10.1016/j.agee.2014.07.024.
- Gorosábel et al. (2019) Evaluating the impacts and benefits of sheldgeese on crop yields in the Pampas region of Argentina: A contribution for mitigating the conflicts with agriculture. Agriculture, Ecosystems and Environment 279:33-42. DOI: 10.1016/j.agee.2019.04.002.

Category (5) Pest species or outbreak overview, if the article reports on general information about one or several species considered to be pests or on specific outbreaks (Lines 184-185).

- Bucher & Ranvaud (2006) Eared dove outbreaks in South America: patterns and characteristics. Acta Zoologica Sinica 52: 564-567.
- Bruggers, Rodriguez & Zaccagnini (1998) Planning for bird pest problem resolution: a case study. International Biodeterioration & Biodegradation 42:173-184.

Category (6): Crop-raider species behavior, if the study focused on the diet or other behavioral aspects of the vertebrate species (Lines 185-186).

- Álamo Iriarte, Sartor & Bernardos (2019) Agriculture in semiarid ecosystems favors the increase fossorial rodent’s activity in La Pampa, Argentina. European Journal of Wildlife Research 65:47. DOI: 10.1007/s10344-019-1281-7.
- Bucher (1982) Colonial Breeding of the Eared Dove (Zenaida auriculata) in Northeastern Brazil. Biotropica 14:255-261. DOI: 10.2307/2388083.
- Calamari et al. (2018) Variations in pest bird density in Argentinean agroecosystems in relation to land use and/or cover, vegetation productivity and climate. Wildlife Research 45. DOI: 10.1071/WR17167.
- Ranvaud et al. (2001) Diet of eared doves (Zenaida auriculata, Aves, Columbidae) in a sugar-cane colony in South-eastern Brazil. Brazilian Journal of Biology 61:651-660.


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: CROP DAMAGE BY VERTEBRATES IN LATIN AMERICA: CURRENT KNOWLEDGE AND POTENTIAL FUTURE MANAGEMENT DIRECTIONS
Review round: 1
Reviewer: 3

Output:
Basic reporting: Thank you to the authors for all the work invested in reviewing this important topic.  Crop damage by vertebrates is a vital issue for both wildlife conservation and human welfare, and so this geographically-focused review has cross-disciplinary relevance.

I believe the authors have slightly overstated the idea that crop foraging is poorly studied.  There have been other recent reviews that are not referenced in the paper but would be of interest, such as:

•	Torres DF et al (2018).  Conflicts between humans and terrestrial vertebrates: A global review. Tropical Conservation Science 11: 1-15.

•	Lindell C et al (2018).  Enhancing agricultural landscapes to increase crop pest reduction by vertebrates.  Agriculture, Ecosystem & Environment 257: 1-11.

•	Hill CM (2018).  Crop foraging, crop losses, and crop raiding.  Annual Reviews of Anthropology 47: 377-394.

This review is still a useful contribution to the literature, however, especially since it focuses on a specific region for which agriculture is particularly important, and the review highlights the uneven distribution of studies across the countries of Latin America.
Experimental design: Your inclusion/exclusion criteria for the systematic review are generally well explained.  Figure 1 especially is very easy to follow.  Where I got a bit confused is in the choice of search terms.  It says that every possible combination of the following terms (lines 161-167) were used, but surely *most* of the output of this method would be irrelevant to the study?  Did you perhaps have these terms grouped into categories (so all possible combinations from each field) or were there literally searches like “Panama AND Honduras”? This section could be explained more clearly.  Likewise, I am a little surprised that this many search combinations over a 40-year period yielded only 59 papers to review.  What was the number of papers generated before the screening steps?

The paper could be stronger with some focus on organization; the results and discussion blend into each other which means at times the paper is unnecessarily repetitive.  As a systematic review (rather than a more general lit review), the results section should be fairly distinct from the discussion.  The first paragraph under “results” (lines 239-246) would probably fit better in the Methods section, and the limitations section (“Quality of information reported”, lines 341-367) would be better suited to the discussion section.

I would recommend something more like:

-Methods (search terms, inclusion/exclusion criteria, number of papers returned, filtering to final sample size)

-Results (key findings, which are currently start of discussion, then sections in order of importance on what crops, what vertebrates, mitigation strategies, location)

-Discussion (lead with most important/surprising finding, talk about limitations of the study or areas for further research, finish with recommendations)
Validity of the findings: The main findings as listed in lines 370-376 are great, but I’d like to see this used more fully for setting priorities in the discussion section.  For example, it’s clear from your data that Rodentia are the most frequently problematic taxon – so what can we do with that information?  How can farmers best respond to rodents, compared to some other type of animals?

The work would also benefit from more nuanced recommendations to reduce crop damage. The authors are absolutely correct in their point that crop protection addresses a symptom and not a cause of human-animal conflict, but recommending further protection of more natural spaces as a solution ignores the importance of conservation in shared spaces.  Farmers and small-scale landowners may have little control over national or global conservation priorities, so what can they do to reduce crop damage on their lands?  Did your review uncover any particularly successful methods, such as planting buffer crops, use of guard animals, or growing crops that are undesirable to the area’s major pest species?

Finally, you’ve highlighted the fact that most of these studies are from Brazil or Costa Rica, and so a broader geographical range is important.  So, which are the priority countries for future study, and why?
Additional comments: GENERAL COMMENTS

Just a thought, and there’s no pressure at all to change it….  In the primatological community, there’s been a movement in recent years to replace the term “crop raiding” with something less value-laden like “crop feeding” or “crop foraging”.  The thinking behind this is that “crop raiding” implies theft, or bad behaviour, or some sort of intent to cause problems for farmers.  I understand this may be more important for primates than for other vertebrates, because primates are so often and easily anthropomorphized, but it’s something you might consider.

A combination of Supplemental tables 1 and 3 would be quite nice in the paper text instead of the supplemental files.

MINOR LINE COMMENTS

Line 51: “all vertebrate orders” – does this mean all 4 vertebrate orders listed a few lines above, all 139 vertebrate orders represented in your sample, or all vertebrate orders in the world?

Line 69: “estimate of 1,591 million hectares” = so, 1.5 billion?

Line 140: Reproductive control is not a lethal method, so this sentence could be phrased more clearly.

Line 176:  Why were only the first 50 records obtained by Google Scholar searches used?  This seems like a flaw in the systematic review method, but if it was part of the selection design it should be justified here.

Line 306: “Of the 114 taxa…”  - please insert “vertebrate taxa” here, because it’s not immediately clear if you’re talking about crops or animals otherwise.

Lines 342-352: I’m not sure the precision of GPS coordinates or the presence/absence of a map in the paper is particularly important for this review.

Line 490: Why was importance values above 10 the cut-off for inclusion in the discussion?  You explained how importance value was calculated in the methods, which is fine, but it might be worth going back to explain why this specific figure is the threshold for “important” in terms of the study’s conclusions.

Figure 4:  Since you have two colours to distinguish between mammal and bird orders, this figure might look at bit better if you put them in a more logical order – either by descending importance value L-R or in alphabetical order.

Figure 6:  The colours in this figure are not distinct enough if people happen to print the paper grayscale like I did.  Could you increase the contrast between the 3 colours?


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: CROP DAMAGE BY VERTEBRATES IN LATIN AMERICA: CURRENT KNOWLEDGE AND POTENTIAL FUTURE MANAGEMENT DIRECTIONS
Review round: 2
Reviewer: 1

Output:
Basic reporting: No comment
Experimental design: The criteria used by the authors discarding technical reports and theses (194-196) and searching only in English terms (lines 180-182) could overlook relevant information for the aim of review the current knowledge of crop damage by vertebrates in Latin America.
In addition that several researches about this topics is lacking still (please, see "Validity of the findings" section).
Validity of the findings: Lines 167-194: Studies about crop damage by vertebrates in Latin America are still lacking.
Just some examples:

When I tried carried out the search in Google Scholar using the terms “Bird + Crop damage + Uruguay”, I obtained as result a research which is not included in the review:
- Olivera et al. (2016) Repelentes de aves aplicados a la semilla de soja: compatibilidad con el inoculante y residualidad en cotiledones. Agrociencia Uruguay 20(2):51-60

When I tried carried out the search in Google Scholar using the terms “Bird + Crop damage + Argentina”:
- Codesido et al. (2015) Relationship between pest birds and landscape elements in the Pampas of central Argentina. Emu 115(1) 80-84. DOI: 10.1071/MU13110

Using the terms “Bird + Crop damage + Costa Rica”:
- Monge (2013) Lista actualizada de aves dañinas en Costa Rica UNED Research Journal 5(1): 111-120. DOI: 10.22458/urj.v5i1.197. In this article, the author carried out a collection of relevant data of several bird species damage on crops. For that, Monge (2013) used literature which in this work (Cuesta Hermira and Michalski) was not cited due to it is considered “grey literature”. I understand that it was their criteria, but if the authors do not use this literature, the aim of review the current knowledge of crop damage by vertebrates in Latin America is incomplete.

“Mammal + Crop damage + Argentina”:
- Jackson (1988) Terrestrial mammalian pest in Argentina - An overview. Proceedings of the Thirteenth Vertebrate Pest Conference 13:196-198. Crabb and Marsh (Eds).

“Vertebrate + Agriculture + Perú”:
- García Mendoza and Prieto Rosales (2019) Análisis preliminar de los daños ocasionados al maíz por vertebrados plagas en la localidad Pilcos, Colcabamba, Perú. Tayacaja 2(1):111-126. DOI: https://doi.org/10.46908/rict.v2i1.43
Additional comments: Additional comment 1: The number of lines that the authors indicate in the resubmission letter is inconsistent with the lines in the tracked changes manuscript. So that, the revision process was difficult.

Particular comments:

Lines 124-142: The bias towards Mammals is maintained. Now, in this new review, the authors included other Vertebrate groups, but the background are about Mammals still. For instance, there is many research with pest birds around the world.

Lines 143-144: In this new review, the number of studies nearly doubled... Do you think that this sentence must remain?

Lines 180-182 and 648-655: The aim of this study is to assess current knowledge of crop damage by vertebrates in Latin America, but the search was only in English. This assumption could did not consider key studies about this topic. Moreover, and considering that “This review can be used by a broad audience, from researchers to conservation practitioners, and from subsistence to commercial farmers” (Lines 160-161), so that, the search should consider Portuguese and Spanish the most common languages in the countries of the study area.

Lines 283-287: The sum of studies is 94, instead of 88.


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

Input:
Title: A WORLDWIDE COMPARISON OF LONG-DISTANCE RUNNING TRAINING IN 2019 AND 2020: ASSOCIATED EFFECTS OF THE COVID-19 PANDEMIC
Review round: 1
Reviewer: 1

Output:
Basic reporting: I think that this section is enough.
Experimental design: Detailed information is given in the method section of the article.
Validity of the findings: The results of the study contribute to the literature
Additional comments: No additional comments


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

Input:
Title: A WORLDWIDE COMPARISON OF LONG-DISTANCE RUNNING TRAINING IN 2019 AND 2020: ASSOCIATED EFFECTS OF THE COVID-19 PANDEMIC
Review round: 1
Reviewer: 2

Output:
Basic reporting: This study employs web scraping, a relatively new tool in the arsenal of sports scientists, to investigate various aspects of training behavior.  The authors have generated search criteria for the largest SoMe database of training and exercise based on a practical benchmark of having run one 6 defined “major” international marathons (3 USA, 2 Europe, 1 Japan). The running behavior (frequency, running distance, running duration) of this cohort was compared across 2019 and 2020 to quantify changes in exercise behavior chronologically aligned with the C-19 pandemic and social distancing restrictions imposed by most of the world.
The main results presented for this global natural experiment were very modest reductions in running frequency and average running duration or distance, but large variation within the comparison years.  Both decreased running activity (early lockdown) and increased running activity relative to 2019 were observed, despite similar restrictions. At a broad level, the data suggest that runners either stopped observing the social distancing rules or found ways to train more within the restrictions.
This study represents a reasonably concise “first pass” analysis of a large cohort of runners.  The authors have made necessary delimitations both in terms of the data search criteria and the specific analyses performed and presented.  The available data from this study would be ripe for additional analyses by scientific peers, thereby further enhancing the value of the methodological approach. For example, my own interests as an investigator of endurance training practice would be to further restrict the cohort to runners who had trained at higher frequencies/volumes in 2019 and then repeated the comparison of training characteristics among “highly motivated” runners who were left without major objective “target races” in 2020.
I found the study to be understandably presented. The authors have contextualized this study within the background of the pandemic and the relatively large set of studies that have been published in a short time around the issue of physical activity changes during the Covid-19 Pandemic.  This is the first study to the authors’ knowledge that compared data for all of 2020 with pre-pandemic data. The literature list is short but includes a review article of 66 published studies investigating physical activity during the pandemic.  Only 4 of these have used objective data (GPS, accelerometry), making this study a unique contribution when combining objective data representing the entire first year of the pandemic (2020).

My general assessment of the manuscript is positive, and I understand the challenges and opportunities presented by this methodological approach.  In some ways, this is a “proof of concept” paper demonstrating the potential utility of web-scraping approaches in the physical activity and sports field (and other social data)
Like all social behaviours, running behaviour is not normally distributed, even within “runners”.  Running volume exhibits a long-tail distribution and it would have been interesting if the authors could show this distribution for 2019 and for 2020 (or by quarters). It seems possible that runners on different positions within this distribution would show different behaviors when faced with both social distancing and cancellation of running events.  In my opinion, this study would be much more interesting if such data were included here.
Experimental design: No additional comment.
Validity of the findings: The authors make all data available via the Github repository and the validity of the findings can be independently evaluated by other investigators.

It would also be useful to know some background regarding the growth of Strava over the timeframe.  Can the authors provide some indicators for how representative was 2019 data alone of “Pre-Covid” conditions?

The manuscript would be improved by reporting the range of years across which the cohort had run at least one major and reported it on Strava?

The average number of training sessions reported on Strava per runner works out to 294 activities across the 2 years.  Please provide the frequency distribution for this metric.

I find the conclusions to be fully consistent with the data analysis presented.
Additional comments: Minor editing suggestions:

L39 ….activity guidelines associated with a reduced risk…..
L41 …suggesting that overall physical activity decreased…..
L42  ….when preventive measures were adapted against COVID-19, such as social distancing and isolation (delete began to be applied, compared to previous periods)
L48  …..review, quantified physical activity in the first half of…..
L68 Our hypothesis was………would be reduced.
L74 Data extraction was performed……
L97 …to search all associated web pages. (delete the rest of this sentence).
L98 and who did not provide information on gender and age group.
L99….we have successfully identified a cohort of distance runners…..
L118 The original dataset analyzed in this study included 37,595 athletes and 14,644,391 separate activity bouts performed in 2019 and 2020.
L156 …differences were not normally distributed……
L166 …the 95%CI ranges were calculated….
L174 …we conducted non-parametric….
L271 During the final months of 2020, running training returned to 2019 levels…..
L276  The reasons for this running rebound are not clear.  We speculate that athletes relaxed their own strict adherence to public policies, or found ways to ……


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

Input:
Title: A WORLDWIDE COMPARISON OF LONG-DISTANCE RUNNING TRAINING IN 2019 AND 2020: ASSOCIATED EFFECTS OF THE COVID-19 PANDEMIC
Review round: 1
Reviewer: 3

Output:
Basic reporting: See notes below
Experimental design: See notes below
Validity of the findings: See notes below
Additional comments: This study analyzed publicly available training records for over 36k athletes, comparing their weekly running volume and duration between 2019 and 2020 to assess the effect of COVID-19. This study used a within-subject comparison and repeated the comparison for each week to counter seasonal and individual variations. Differences in weekly training volume and duration were found in March (onset of restrictions amid the pandemic) and the largest differences were recorded in September.

Overall
Strength:
This study made use of an open dataset with real-world training record, which is appropriate for this type of studies (i.e., understanding changes over a period of time). The authors reported details on how participants were selected, using available data to set and screen for participants based on the inclusion/exclusion criteria. They have also performed
sub-group analysis (age-group and gender) and provided details for how they obtain (and estimate) the age group of athletes based on available records. The methods used in this study could be referenced in future studies.

Limitations:
While I understand the difficulty in screening participants based on available data, the inclusion criteria have limited the generalizability of the findings, only runners who have completed a marathon (out of the 6 major marathons) were included.

The authors reported a 3.6% reduction in athletes training (and up to 16% in certain weeks). This decrease is inherent, as they have excluded runners who did not run in 2019 but in 2020. There can either be no change or a decrease, and without a figure for comparison (e.g., 2018 vs. 2019), it is impossible to interpret if the change is likely due to the pandemic or not, as there are other possible reasons for runners to stop running (i.e. injury).

There is a lack of discussion on the significance of the study. Results of the analyses were reported without connection to COVID-19. The Stringency Index could be used to help better understand the effect of COVID-19. If possible, the authors could analysis the difference between locations with high Stringency Index to see if there is any relationship between the severity and the changes observed in running volume.

Introduction
I suggest the authors elaborate on the shortcomings/limitations of previous studies to further strengthen the need of the current study. It was mentioned within the introduction that previous studies relied on questionnaires (line 47) and Strava included new users in 2020 (line 55 -57), but they did not explain why that would be substandard for answering the research question. The knowledge gap has to be better defined and how the current study design is more appropriate should also be explained.

The reason why long-distance running was used as a measure of physical activity was only briefly mentioned in the last paragraph of the introduction (line 65 – 76). This study is primarily study changes among long-distance runners, the authors should consider shifting the focus onto long-distance running rather than physical activity. There are published studies on how running habits changed during the pandemic, the authors should mention that instead of only focusing on physical activity within the first 2 paragraphs of the introduction.

You may wish to include this recent publication from Chan et al:  (https://www.frontiersin.org/articles/10.3389/fspor.2021.812214/abstract) in the Intro and Discussion.

Methods
The methods section included enough details and was written clearly enough for reader to follow. The study design and analyses can potentially be referenced in future studies.

Results
The authors may want to calculate Age-Grade levels for these runners, based on their finish time for the marathons and their age (Clermont et al., J Appl Biomech. 2019:1-9. doi: 10.1123/jab.2018-0453).  This may help put the results in perspective for the reader and provide further insight into the results.  The age-grade for the runner may also provide new sub-groups for comparison.

Section 3.1 might fit better in the methods or as supplementary material.
If possible, present number (value and % changes) in a tubular format for clarity.

Figure 1 and 2 both contains a lot of information and look very busy to a reader. The authors may consider:
1.	Putting the stringency index in a subplot above the training volume/duration.
2.	Removing the number of athletes (red line) from either one of the figures. They are the same and do not add more value when presented on both figures.

The blue shaded area (assuming it is the 95% CI of the change in weekly running volume) is only visible on graph D and G.
There are 2 rows of light blue bars on each graph, are they both indicating statistical differences?

Line 236 - 237: speculation and interpretation of the results would fit better in the discussion.
Line 237: Statistical test used for analyzing association between the stringency index and running volume was not mentioned. If the association is determined by observation, please specify.

Discussion
Overall, the discussion can use more elaboration on the practical implication of the study. Results are presented and repeated in the discussion, but there is a lack of comparison with other studies or other physical activities. The significance of the study to future research and athletes should also be discussed.

Line 260 – 264: “running training and number of athletes running … do not seem to have been much affected by COVID-19…” this interpretation needs to be supported.

The inclusion criteria (i.e., only marathon runners) should be justified. I understand the need for the delimitation (as mentioned in line 95). I suggest discussing the feasibility (and difficulty) of including recreational (non-competing) runners within the discussion.

The authors have averaged (weighted) the stringency index based and presented the overall change of training volume between 2019 and 2020. A location-specific (or grouping based on stringency index) comparison might further reveal the effects of COVID-19.

Line 293 – 297: the change in motivation and the effect on race cancellations has been studied qualitatively. The authors may reference other studies (i.e., https://doi.org/10.1371/journal.pone.0246300) to support their speculation.

Conclusion
The association between irregularity in running training and injury should be mentioned in introduction and discussion.


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

Input:
Title: A WORLDWIDE COMPARISON OF LONG-DISTANCE RUNNING TRAINING IN 2019 AND 2020: ASSOCIATED EFFECTS OF THE COVID-19 PANDEMIC
Review round: 2
Reviewer: 1

Output:
Basic reporting: The authors have done a nice job addressing our concerns and suggestions.  One last item that needs to be addressed is on line 346 of the Discussion which states: "...without recruitment (almost in a prospective way). "  Please eliminate "(almost in a prospective way)." as this is not appropriate nor correct.
Experimental design: N/A
Validity of the findings: N/A
Additional comments: N/A


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: BENCHMARKING METAGENOMICS CLASSIFIERS ON ANCIENT VIRAL DNA: A SIMULATION STUDY
Review round: 1
Reviewer: 1

Output:
Basic reporting: This paper reports a simulation study conducted with four bioinformatics tools widely used to taxonomically classify metagenomic reads. In this study, the authors used 120 viral sequences and simulated different features that are commonly found in ancient DNA, including different level of fragmentation, deamination damage, sequencing errors and presence of human sequences. The topic of the manuscript is very interesting and relevant, especially when considering the recent advances in ancient DNA sequencing methods.

The article is very well written and clear, the methods are based on previously described techniques, and tables and figures are relevant and properly presented.

Reading the text, several questions arose in different parts, but most of them were addressed in the subsequent sections of the manuscript.
Experimental design: In general, the work has been correctly designed and conducted. However, there are some methodological aspects of the work that are worth to be commented here (and better covered by the authors in the text):

1.	Program’s parameters

The authors compare four different tools (the so-called ‘classifiers’) in regard to their performance under different conditions usually found in ancient DNA samples. It is clear that there are many variables to be assessed and this aspect restricted the possibility of testing different parameters for each program, so default parameters were used throughout the study. Nevertheless, this choice has clearly impacted the performance of these tools under the tested conditions, as is clear in the case of DIAMOND and Kraken2 (please see comments in the next item).

2.	The authors chose to randomly select 120 reference viral sequences from RefSeq, including complete genomes, genome segments, and CDS. This choice, while randomly made, may have left some important viral groups out of the analysis. I would rather choose the most relevant viral genomes in terms, paying special attention to some features: (1) for multisegmented genomes, are all segments represented? (2) and; is there a good representation of all Baltimore groups? Please justify why they have chosen randomly selected sequences instead of ensuring that all viral groups and segments would be represented in the reference dataset.
Validity of the findings: I will comment below on some results that I believe should be better treated or at least discussed more deeply.

1.	One aspect not raised by the authors is that given the high evolution rate of viruses, higher taxonomic levels show conservation restricted to some relatively short regions, those that are under strong selection pressure. Conversely, lower levels (more specific) tend to show longer conserved regions certainly impact the overall performance of tools that use different approaches to classify sequences. More divergent sequences (belonging to higher levels) probably show overall higher heterogeneity of kmers, while still maintaining conserved stretches that can efficiently be detected by a sequence aligner such as DIAMOND, thus explaining why this program shines in the ‘correct higher’ category. This aspect should be better covered in the Discussion.

2.	It would be very interesting if the authors could provide some clues on why some viruses have shown poorer classification for some of the tested programs. For instance, would they show different compositional biases, do they belong to viral groups that show higher evolutionary rates (e.g. RNA viruses), etc.

3.	Regarding multisegmented genomes, let’s take as an example the case of the Bunyavirales (e.g. the genus Orthobunyavirus). These viruses show a tripartite genome, with segments coding for the RDRP (L segment), the nucleoprotein (S segment) and Gn-Gc glycoprotein (N segment). It is well known that the L segment is much more conserved than the S and N segments. I would be very interesting to assess how variable is the performance of each classifier for these viruses, taking into account the different segments. This is an example on how interesting and appropriate a rational choice of the viral sequences used in the reference dataset would be.

4.	Another important aspect regards retroviruses and HERVs (human endogenous retroviruses). Considering that the human genome does contain a large collection of these elements, which show cross-similarity to exogenous retroviruses, this condition must have strongly impacted the performance of the classifiers, especially when considering that there was no specific methodological step to deal with this problem. This topic should be much better explained and discussed than presented in the Discussion (lines 658-662).

5.	A noteworthy result is the finding that DIAMOND shows relatively poor performance for the correct species assignment while displaying much better results for higher taxonomic levels (lines 319-323). Using default parameters was certainly a limiting factor for a good performance of DIAMOND and Kraken2 in some tests. Having admitted this fact (lines 589-596), the authors should refrain from being so emphatic in their conclusions:

“Nevertheless, short reads cannot be handled by either Kraken2 or 683 DIAMOND” (lines 682-683).

These programs certainly can deal with short reads, but require using the most appropriate parameters rather than the default parameters.
Additional comments: No comment.


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

Input:
Title: BENCHMARKING METAGENOMICS CLASSIFIERS ON ANCIENT VIRAL DNA: A SIMULATION STUDY
Review round: 1
Reviewer: 2

Output:
Basic reporting: In this study, entitled “Benchmarking metagenomics classifiers on ancient viral DNA: a simulation study”, Arizmendi Cárdenas and colleagues explore the performance of four metagenomic classifiers for detecting ancient viral reads, to assess their potential for being used in future palaeomicrobiological studies. After a number of tests, assessing the effect of potential aDNA substitutions, read length, and human DNA within specimens, the authors conclude that out of the tools Centrifuge, Kraken2, DIAMOND and MetaPhlAn2, Centrifuge would be the best performing tool and most applicable for short-read ancient DNA data. The paper is written well and the scientific goals of the study are made clear throughout the introduction. Regarding the study’s background, one point of improvement within the introduction concerns proper citation of relevant literature. The authors should mention previous attempts on comparison of metagenomic classifiers for ancient pathogen detection as, currently, no such citation is provided. Moreover, certain publications could be re-considered, as they are inappropriate as references to some of the discussed concepts. For more specific comments, refer to the sections below.
Experimental design: Importantly, in terms of the investigation’s scope, while such a study is appreciated and needed within the community of palaeomicrobiologists, as so far similar assessments only exist for ancient bacterial sequences, there are several concerns that arise about the study’s design and, as a result, outcome. Below you can find a number of general suggestions, as well as specific comments, that should be addressed in a new version of the paper.
Validity of the findings: no comment
Additional comments: General comments:

1. One of the classifiers chosen to be tested by the authors is DIAMOND. DIAMOND is a taxonomic binning tool operating under an amino acid database. The developers of DIAMOND have more recently released the tool MALT, whose concept of taxonomic binning is very similar to DIAMOND, but operating under a nucleotide reference database. MALT (Vagene et al., 2018) has been often used to detect bacterial and viral sequences from ancient human remains and has been developed further within the pipeline HOPS (Hübler, Key et al., 2019) to tailor the postprocessing of results for aDNA-aware assignments. Given the abovementioned characteristics, why do the authors choose to include DIAMOND in this comparative assessment study instead of MALT? I suggest MALT be considered as a more appropriate tool for this comparison. This is particularly important especially in light of the author’s finding of DIAMOND’s poor performance in classifying 30bp reads, which are typical of endogenous ancient DNA.

2. The authors mention within the methods section that viral sequence datasets were generated to contain 10x representation of each virus. Such a viral coverage goes beyond what is expected from ancient metagenomic samples, especially for shallow-shotgun sequenced libraries that are usually used for pathogen screening. For example, a recent study by Muehlemann et al., 2018, on HBV evolution showed that as little as two viral reads were detected in shotgun-sequenced ancient specimens prior to hybridization capture. Therefore, I suggest that tests be performed with a significantly lower representation of target viral reads within the simulated datasets, similar to previously presented results of ancient DNA studies.

3. Moreover, the highly dominant environmental background, which is typical in ancient metagenomic specimens, is not included within the simulations performed in this study. Environmental contamination is one or the most typical characteristics of ancient metagenomic specimens, and one of the main complicating factors associated with ancient pathogen identification by metagenomic classifiers (discussed in detail in the review by Warriner et al., 2017). I suggest that tests be altered to better reflect true metagenomic data deriving from ancient specimens. Moreover, I suggest that target viral reads occupy a small percentage within those datasets, <0.1%, to reflect typical ancient pathogen endogenous DNA estimates. Such simulations can be performed within gargammel that is already used by the authors to simulate aDNA damage in this study.

4. The authors describe that “A total of 120 reference viral sequences were randomly selected from the viral genomic NCBI RefSeq database”. Here, the authors should provide the entire list of viral sequences that went into this simulation study. Moreover, the authors should elaborate on the reasons of why a random selection process was used, whether viral genomes previously detected by aDNA studies were included in their list, and whether the list was restricted to DNA viruses only or also contained human-infecting RNA viruses.

5. Regarding the incorrect read assignments (Figure 4C, 5D, 6D, 7D) it would be critical to investigate whether these tend to always be from specific viral sequences that appear to be more difficult to classify than others, for example from viral taxa with high genomic diversity.  Moreover, where do the “incorrectly assigned” reads end up? Do these end up on higher taxonomic nodes because of their conservation among several taxa? Specifically, it would be important to check whether “incorrect assignments” are most often seen on over-represented taxa within the reference database. Results from this test could inform on the importance of balancing database entries for future studies.

 6. The authors restrict their assignments to read thresholds higher or equal to 50 reads, in order to avoid spurious read assignments. However, recent studies have shown the detection of ancient DNA viruses with fewer than 10 reads, both for larger DNA viruses (e.g. Variola, see Muhlemann et al., Science 2020) as well as for DNA viruses with shorter genomes (e.g. HBV, see Muhlemann et al., Nature, 2018). How are the present findings corroborated in light of the recently published literature?

Specific comments:

-	The authors state in their Introduction “The availability of aDNA has opened a unique window into the past allowing for instance to pinpoint the origin of a pathogen (Taubenberger et al. 2005; Mühlemann, Jones, et al. 2018; Rascovan et al. 2019)”. This sentence should be altered since none of the cited papers has effectively pinpointed the origins of any of the studied pathogens. Within this context, it might be worth to mention the oldest recovered viral genome, which to data is the one presented by Krause-Kyora et al., 2018.

-	In order to reflect the potential of ancient pathogen studies, the authors state in their Introduction that such data are able to “…to characterize past epidemics and the prevalence of pathogens across time (Mühlemann, Jones, et al. 2018)”. This sentence and citation should be revised, as the cited research does not reflect the characterisation of a pandemic, and “prevalence” is an epidemiological measure that cannot be estimated using ancient DNA due to inherent data biases.

-	“Additionally, HBV’s prevalence across time was found to vary from the Bronze Age to Middle Ages across space (Mühlemann, Jones, et al. 2018).” Please correct the statement on “prevalence” as discussed above.


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: BENCHMARKING METAGENOMICS CLASSIFIERS ON ANCIENT VIRAL DNA: A SIMULATION STUDY
Review round: 1
Reviewer: 3

Output:
Basic reporting: The manuscript from Arizmendi Cárdenas et al. presents a benchmarking study aiming at identifying the most suitable tools for the detection and taxonomic classification of viral sequences in ancient DNA datasets. In the study, they test four softwares (Kraken2, Centrifuge, DIAMOND and Metaphlan2) with simulated sequencing data with aDNA degradation signatures produced from 120 randomly chosen viral genomes. They present different metrics to assess their capacity to detect these viruses (precision and sensitivity) as well as their false positive and false negative rates. Although the question behind the study is valid, I find that the work has several major flaws that must be addressed.

Major points:

-	The study types for which the benchmarking is tailored is not clear.
The manuscript is presented as aiming at detecting any kind of virus in ancient DNA data (RNA and DNA based), and the focus continuously change along the manuscript (i.e., in some sections they seem to be focused on ancient human pathogens, in others in animal infecting viruses, etc.). However, depending on the kind of virus that are searched in a study the appropriate methods for the analysis will be different. In that sense, it is not possible to benchmark methods universally, to deal with every type of study. In that sense, the manuscript does not properly test the methods for different kinds of situations and does not discuss either in which kind of situations each of the tested methods could work better. For instance, how good these classifiers are for detecting known human infecting viruses, to detect animal infecting viruses, to detect known phages from the human microbiome, or phages in general, or viruses in a non-human ancient sample (animal, plant, sediments, etc.). These categories I am listing are just illustrative (I don’t pretend you to use them as such), I am just saying that depending on the goal of the project, the kind of viruses that one would like to detect are different and as well as the appropriate methods to detect them.

-	I have several concerns with the testing dataset of 120 viral genomes.
First, the list of genomes used in this dataset is not given. Second, it is neither explained how was the random sampling done. One would expect that certain viral groups are overrepresented respect to others.  Third, and related to my previous point, the selection of the viral genomes should respond to an a priori question, i.e., which kind of viruses would you be interested in searching in an aDNA study? From my point of view the choice of a random set of genomes from all known viruses does not reflect the kind of things that are investigated in most aDNA studies. Fourth, I don’t understand the choice of including genome segments and coding sequences… Most likely for such cases there will be a whole genome of the same species in the database that should be used instead. The fragmented nature of aDNA data should be modeled by generating very few reads from these genomes, not by using incomplete sequences as starting point to generate simulated reads.

-	The tested methods and the databases used were not correctly chosen.
First of all, MetaPhlan2 was not a suitable method if any virus in RefSeq was to be tested. Viruses don’t have universal marker genes as cellular organisms, so it is not possible to use it for viral detection. The authors themselves show that two thirds of the tested viruses could not be detected, which was absolutely expected even before running any test. For the case of DIAMOND, the only way to directly test sensitivity, precision and incorrect classifications compared to Kraken2 and Centrifuge was to use the exact same database as in these methods (i.e., either all with the full RefSeq DB, or all with a viral DB). I think the full RefSeq DB for the three is the best choice, because it can reduce false positives. And coming back to my first point of the type of study, if we were trying to characterize an environmental virome, where most viral genomes won’t be likely present in the DB, DIAMOND would be a better choice, because it has the highest precision (Fig 4A) and its protein level analyses with SEED extension and LCA approach will allow classifying genomes that are more divergent from those in databases with much better resolution than k-mer based methods (which will fail at classifying a certain taxon if it’s full of synonymous mutations). K-mer based approaches on the other hand would be a better choice when a specific well-known species is searched (e.g., a DNA viral pathogen such as HBV or variola), although in those cases just mapping reads (with bwa or bowtie) to the reference viral genomes would be even better.  On the other hand, if you were looking for human viruses related but not identical to those in databases, you should have chosen viral genomes for such case.
For instance, if you were using a RefSeq database from before 2018-19, you could have tested Sars-CoV-2 among your 120 test viruses, which would inform on the best method for this kind of cases. This is relevant for aDNA, because we may be searching for viral species from certain viral pathogen groups that were infecting populations in the past and are now gone.

-	Simulating reads covering viral genomes at 10X does not really represent what would happen in an aDNA study. Indeed, the most typical problem is that there are only few reads of a certain microbe (e.g., mean coverage at 1X or less), so we must identify their presence with highly fragmented data. Hence, I think that different coverages should have been tested. I believe that at very low coverage, the effect of deamination and sequencing error may become more evident.

-	The manuscript is unnecessarily long.
The manuscript has 22 pages, where the same content could have been described in 5 or 6 pages. There are too many sections in results and discussion that could be collapsed, and the authors repeat themselves a lot (e.g., the discussion section repeat a lot what has been already said in the results), while not discussing properly some relevant points. I think that Results and Discussions should be presented together. For instance, I was having concerns or thoughts about certain results, which were finally addressed in the discussion many pages after.

Altogether, I think that the manuscript needs still a lot of work and to address these major points before being considered for publication.
Experimental design: There are some major problems in the experimental design, as listed in the Basic reporting and the general comments to authors. Some of these include:

-	Issues in defining the scope of the work (i.e., which kind of aDNA studies and kind of viruses are tailored)
-	Issues with the choice of viral genomes for the tests, and the coverage used for the simulated reads
-	Issues with the selected methods and the databases used for these methods, that complicate the comparison of results
Validity of the findings: Because of these flaws in the experimental design and definition of the scope, the findings are not very conclusive, and it would be hard anyway to drive any conclusion. There are also issues in how results are discussed (e.g., in which case each method would be better).
Additional comments: Then I also made several comments while reading the manuscript, which I list in order of appearance:

Abstract: There is a very frequent use of the present tense. I believe the past tense would be more accurate, because you are talking about the work you did.

Line 32-33: Do you have any reference to support this: “making the identification of ancient viral genomes particularly challenging”

Intro: I think the paragraph from L67 to L84 could be reduced to just one sentence to mention that recovery of ancient viral genomes is possible, then the citations, but for the scope of the article, the particular examples are not relevant.

Lines 96-106: This paragraph about the characteristics of aDNA can be also drastically reduced to just the main key points. For the sake of this work, the only important are the C-to-T/G-to-A transitions, the shortage of read lengths and maybe something on the quality.

Line 180 and related to major point 2): I don’t understand the rationale behind the choice of the 120 genomes. I got several questions while reading this. For instance, the world virosphere is extremely large, and highly under sampled, mostly if we consider phages. However, the human virosphere is much more characterized, and especially if we consider the human infecting viruses, and even more if we consider the pathogenic ones. So, which of these levels are your main targets? Your introduction seems to point towards an interest in human pathogenic viruses, but your dataset of 120, although not shown, seems to be for any virus.
In that sense, rather than just 120 random viral genomes based only in their genomic length, I would have taken random representatives of these heterogenous groups. When it comes for aDNA data, it won’t be the same to classify ancient phages in the microbiome, than ancient human infecting viruses. Moreover, I did not find the list of the 120 viral genomes anywhere (maybe I missed it). This should be shared, at least as a supplementary table. I wonder at which extent this random choice is not biased by the fact that certain viral groups are far more represented in NCBI database than others (e.g., today there are more than 500k genomes of Sars-CoV-2 alone).
Also, RNA viruses are in principle less relevant since they are generally not tackled in aDNA studies, since no one is really sequencing ancient cDNA. You can test with few, in the case anyone tries it in the future, but we can all agree that this is not a common practice in the field.
Finally, having so many whole genomes in databases, I don’t see the point of including the segments and CDS. What do you gain from that? This does not reflect the kind of data you’ll get from an ancient sample, and for most cases, you will have a close related genome in database you could use instead.

Line 200-201: You should mention here that other qShift values were also tested, which is mentioned after.

Lines 203-206: What’s the rationale behind the choice of 10X for the reads. In an aDNA study such a high coverage is rarely the case. Moreover, wouldn’t you want to know whether the virus can be correctly detected and classified when you have only few reads from it?

Lines 219-224: Why DIAMOND was not used with the same or similar RefSeq DB as Kraken and Centrifuge? By just using the viral genomes, you can get false positives (sequences that otherwise would be misclassified) and you can also overlook the false negatives it could give. Indeed, when looking at figure 4A, Kraken and Centrifuge show practically identical results and I just wonder if results with DIAMOND would not improve to some extent if we were using the same database as with Kraken and Centrifuge.

Lines 225-228: I don’t quite see the point of including MetaPhlan2. The analyses presented in the manuscript are tailored at detecting any kind of virus, not some particular groups that have marker genes. There are not many conserved genes in viruses, hence only a very limited group of viruses can be detected (those groups that are better characterized and contain marker genes). In that sense I am not sure at which extent it can be compared to the other methods for the viral dataset you used for benchmarking.

Figure 1: In the “molecule” field for the database, you should use “nucleotide”, since you are also including RNA viruses in the database.

Figure 3: Here we can see that substitutions due to deamination do not reach the average mean of 1 per 600bp with any deamination probability tested. I wonder if this is what we would normally expect at maximum in an ancient viral DNA, based on other literature examples. From Figure 3B, it seems that sequencing error would exceed the number of mutations due to deamination at qshift 11. This is reflected in Figure 6 and 7, where results barely change for deamination (probably because there are not really many mutations introduced) and do decrease a bit due to sequencing errors. I would nevertheless mention upfront which are the viruses that are no longer classified in each case to try to understand which are the features or cases in which each software is most sensitive. Some mentions to this are given, but way after in the text.

Figure 4B: You should also mention upfront which are the viruses that are not detected (i.e., there is one virus missing from Kraken2, Centrifuge and DIAMOND, but it is not the same one for DIAMOND. The identify of these viruses should be mentioned before in the text. Also, how would you explain the decrease in “# of viruses detected” on DIAMOND when increasing the reads size threshold?

Line 296: Human simulations.
I believe that the reads that fail to be removed from aDNA data are not at any random region in the human genome. In that sense, instead of testing reads from any region of the human genome, I would have used human sequences that failed to map into the human reference genome, which are in fact the ones that are likely to escape the human cleaning step.

Figure S2: Both DIAMOND and Metaphlan2 show a high number of reads non classified. This is certainly expected, since DIAMOND would only use information from protein coding genes, and Metaphlan2 only marker genes. Any read not mapping into these subsets, will therefore not be classified. However, this does not mean the method is less useful depending on what the goal is (e.g., retrieving all reads from a detected viral pathogen or getting an idea of the whole viral diversity in the sample, etc.). Maybe a way to overcome this issue would be to additionally calculate sensitivity and precision based on total classified reads, not only on total reads (i.e. not counting the unclassified). This analysis will certainly favor DIAMOND followed by Metaphlan2, because they have less proportion of “incorrect” reads (as you mention also in L344-345).

Line 329-331: Would the proportion on “incorrect” reads change if you were using the whole RefSeq DB for DIAMOND? Maybe the fact that there is a higher proportion of “incorrect” in Kraken2 and Centrifuge is just related to the larger database that it was used with the latter methods (e.g., viral sequences misclassified as some bacteria or eukaryote that were not present in DIAMOND DB). In that sense, which kind of viruses were exceeding the 60% “incorrect”?

Lines 373-393: The number of spurious taxa in this paragraph are confounded by the fact that a different database was used for DIAMOND. L390-393: these thresholds are nearly impossible to establish universally because there is no way to predict how well a viral DNA will be conserved in an ancient sample.

Line 403-404: As it is also acknowledged by the authors, this was simply because of an error when building the databases or when choosing the read lengths for the tests. If you would have used a k-mer size of 27 to build the database, it would have worked, but then the other results may have changed with shorter k-mer sizes. Same case for DIAMOND. This is not a result to discuss in the article in the way you did, this is simply an error in the experimental design. Again, the comment remains the same, things should be compared with equivalent parameters every time is possible.

Lines 534-540: This result is not discussed. It is probably due to the presence of human sequences in these RefSeq genomes? Low-complexity sequences? What?

The Discussion is too overlapping with the results section. I would recommend to present results and discussion together to save space and also because some of the results need to be discussed while describing them.

Lines 577-596: As I said before, it is wrong to say that Kraken cannot lead with short reads. You should had built the database with a k-mer size according with the read lengths you were going to test.

Line 610-612: it is because many viral groups don’t have a marker gene.

Line 613-621: The discussion about DIAMOND is somehow wrong. Proteins have less variability than DNA, because the genetic code has many synonymous, so different DNA sequences can give the same protein. Also, you should discuss here in which cases DIAMOND could be more suitable.

Lines 626-629: I don’t think that deamination at 0.5 is comparable to qShift at -11. While deamination 0.5 may add one to no mutations, qShift -11 adds more than one. The results obtained is just a consequence of using a very high error rate, and a modest deamination probability.

Lines 630-633: I don’t understand this conclusion. It looks contradictory to what you said right before.

Lines 634-648: As I mentioned before, comparing Kraken2 and Centrifuge on all RefSeq, while DIAMOND in only viruses is a mistake that turns them hardly comparable.

Lines 673-677: Here you are mixing things, I think. If you were looking for specific ancient viral pathogens species (as in both papers cited here), you can simply map with bwa or bowtie on a database of known viral pathogens (an analysis that surprisingly you did not benchmark). So, this comes back to my main comment at the beginning, depending on the type of study, different strategies could be better. Here you are just focusing on one, so which case are you interested in?

Line 697-700: As I said before, most people remove the human genome prior to the analysis of microbes, hence you should perform the analyses with the human reads that remain after mapping to the reference (there is always a fraction that get not mapped).

Lines 705-707: This is a surprising statement to conclude the article! The benchmarking presented in this paper is tailored to which cases? If we have to benchmark again for our particular studies anyway, what’s the purpose of this article then?


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: BENCHMARKING METAGENOMICS CLASSIFIERS ON ANCIENT VIRAL DNA: A SIMULATION STUDY
Review round: 2
Reviewer: 1

Output:
Basic reporting: The authors submitted an extensively revised article and answered all my questions satisfactorily. Many experiments were redone and some new ones were included. In addition, the text was also greatly changed in order to meet all the points raised. I consider the article to be suitable for publication.
Experimental design: All points raised in my previous review have been addressed.
Validity of the findings: Changes made to the text and new experiments are in accordance with the findings and their interpretations.
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: GENOME-WIDE CHARACTERIZATION AND EXPRESSION OF THE TLP GENE FAMILY ASSOCIATED WITH COLLETOTRICHUM GLOEOSPORIOIDES INOCULATION IN FRAGARIA × ANANASSA
Review round: 1
Reviewer: 1

Output:
Basic reporting: The introduction section needs to provide, generalized background of the topic and explanation for why TLPs are highly complex gene family. However, to make the manuscript more substantial, the author may need thorough polishing of English. I suggest major revision before accepting for publication. Some more comments are mentioned below
I)	Rephrase line 124-125  shock
II)	Figure 1A needs to be more legible
III)	In Table 1 the information of chromosome needs to be incorporated
IV)	Rephrase line 194-197
V)	Rephrase line 206-210
VI)	Line 239, FaTLP68 is predicted as calmodulin-binding receptor-like cytoplasmic kinase 2 isoform X2 and not as TLP. If it is not TLP then why the authors have selected these gene for further validation.
VII)	Raw data of qRT-PCR not cited in the manuscript
VIII)	Line 276, Shatters et al., 2006 is missing in reference
IX)	Discussion section needs to be improved further, especially for phylogenetic and motif studies
Experimental design: I think the motivations for this study need to be made clearer. In particular, the connection between the phylogenetic and motif analysis, and the gene expression, could be clearer. One way to demonstrate this connection would be to relate which phylogenetic clade genes have higher infection due to C. gloeosporioides infection. Furthermore, I was also wondering why the author chose outdated neighbor joining method for the construction of phylogenetic tree, the author also offers no explanation of why he included FaTLP68 for expression study, even though it was not annotated TLP.
Validity of the findings: The authors reported TLP genes in Fragaria ×ananassa and their importance for defense against  C. gloeosporioides which seems interesting Genome-wide identification of these TLP reported genes might be helpful for future research.
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: GENOME-WIDE CHARACTERIZATION AND EXPRESSION OF THE TLP GENE FAMILY ASSOCIATED WITH COLLETOTRICHUM GLOEOSPORIOIDES INOCULATION IN FRAGARIA × ANANASSA
Review round: 1
Reviewer: 2

Output:
Basic reporting: The manuscript submitted has an acceptable level of English however, there were some lagging space in the manuscript, therefore, suggested to go through the manuscript before final submission for some grammar and technical errors in the word file.

Line 228-234: In addition to the numbers of gene also mention their percentage as well in brackets.

Line 289-290: Not all six genes overexpressed in resistant cultivar, FaTLP62 upregulated in susceptible cultivar only. should be rephrased
Experimental design: 1. The comparative phylogenetic analysis carried out to identify the functional relationship of strawberry TLPs with TLPs from A. thaliana and O. Sativa could be explained more.

2. The distribution of FaTLPs on the 24 chromosomes need more explanation as why in most cases the same group is scattered on the different chromosomes. Is this the same with A. Thaliana and O. Sativa?
Validity of the findings: Line 228: Why more genes were upregulated in susceptible genotype compared to resistant one? Can you explain it more with any reference?

Line 278: explain further with reference.
Additional comments: No additional comments