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: DOES TWITTER LANGUAGE RELIABLY PREDICT HEART DISEASE? A COMMENTARY ON EICHSTAEDT ET AL. (2015A)
Review round: 1
Reviewer: 3

Output:
Basic reporting: The manuscript is well written in clear, unambiguous, professional English language. Intro and background show the context, and the literature is well referenced and relevant. The structure of the manuscript is also clear, figures and tables are relevant. Raw data are supplied. Indeed, the reanalysis is extremely transparent, all data and scripts can be found on OSF, supplemented with a very helpful code and data documentation.  I partially checked the raw data and scripts and could easily reproduce the reported results.

However, when I read the manuscript, I also observed that some issues appeared twice in the manuscript, once in the introduction and once in the results section. I had the feeling that this might not be the easiest structure for a reader to follow, and that it might be good to restructure your manuscript a bit to increase its accessibility.

The current structure is
A) Introduction
    A1) General Introduction (lines 36-63)
    A2) Problems that occurred from reading the original article (lines 64-241)
B) Method (lines 242-166)
C) Results: Problems that occurred from the reanalysis (lines 268-528)
D) Discussion (lines 529-622)
E) Conclusion (lines 623-639)

In my view, the problem is the separation of part A1 (Problems that occurred from reading the original article without looking in the data) from part C (Results: Problems that occurred during the reanalysis). This separation has the disadvantage that many of the issues appear twice in the manuscript (usually, the second time with an introducing sentence such as “As previously noted…”, “We noted earlier…”, etc.). I think that it would be easier to follow for the reader when each issue would be handled only once, and I would thus suggest that you move some of the parts of A2 to the Results section.

Specifically, I suggest moving lines 100-112 of the part “issues related to the etiology of AHD” to the beginning of the part “variability in ICD-10 coding of cause of death” (lines 282ff.), because both sections deal with the unreliability of the physician’s diagnosis of AHD mortality. Lines 113-133 of this part would then fit to the beginning of the part “Use of mortality from AHD as the outcome variables” (lines 307ff.), because then the introduction of the idea of analyzing suicides and the actual analysis of suicides comes together in one section. The part “issues associated with considering counties as communities” (lines 186ff.) would well fit to the part in the results section titled “problems associated with considering counties as communities” (lines 386ff.). As you even see from the titles, both parts deal with exactly the same topic, and I think that it would be easier for the reader when you provide your critique of counties that is independent from a re-analysis together with the critique that depends on your re-analysis. The “possible sources of bias in the geographical coding of Twitter data” (lines 151ff.) and the “potential source of bias due to derivation of topics with Facebook” (lines 169ff.) could similarly go together with the part “bias caused by selection of counties” (lines 365ff.). For the reader, it does not make a big difference whether you observed a bias by carefully looking at the supplement or by looking at the data.

I want to end this by saying that this re-structuring is just an idea and that there might be very good reasons why you chose the current structure. I just had the feeling that your manuscript would be more accessible with a changed structure, but it is absolutely fine with me if you keep the structure as it is.
Experimental design: The research is within the scope of the journal, as it deals with an important health issue. The research question is well defined, relevant and meaningful. The analysis was performed rigorously to as high technical standard. The analyses are described in sufficient detail and all information to reproduce the results is provided.
Validity of the findings: Data is robust, statistically sound and controlled. Conclusions are well stated, linked to original research question and limited to supporting results. Speculation is identified as such.
Additional comments: I read your manuscript “No evidence that Twitter language reliably predicts heart disease: A reanalysis of Eichstaedt et al. (2015a)” with great interest. This manuscript reports a reanalysis and an extension of an original manuscript “Psychological language on Twitter predicts county-level heart disease mortality” by Eichstaedt et al. published in Psychological Science. The original article reports that the language used on Twitter, aggregated at the level of U.S. counties, predicts county-level mortality rates from atherosclerotic heart disease (AHD). Surprisingly, not only could the authors find evidence for the effect of language, but they could even show that Twitter language predicted AHD mortality significantly better than a model combining socioeconomic and health risk factors, including smoking, diabetes, hypertension, and obesity. This result has possible societal implications, which is mirrored by the fact, that the article has already been cited 173 times in only three years. One could be a bit skeptical about the findings in Eichstaedt et al. (2015), given that the two most important results are only significant at p = .026 (incremental validity of Twitter over and above traditional risk factors) or p = .049 (comparison of Twitter model to traditional risk factor model).

Indeed, you now identified in your manuscript a number of factors that question the result by Eichstaedt et al. (2015). At first, I would like to thank you for the work you put into the reanalysis of Eichstaedt et al.’s study. It is important for the field that published studies are checked critically. This is exactly how science should work, but which we do not see that often in psychological and medical research.

Taken together, your new analyses and arguments make me doubt that the original finding is as robust as Eichstaedt et al. (2015) stated in their original publication. For me, the most important points were the severe problems with the data that you identified. In particular, problems in the coding of AHD mortality, as shown by a range from 1.55% to 26.11% between counties, which is a far more extreme range in the main dependent variable than I would have expected – and which is not plausible to me at all. Furthermore, the extreme differences in population size between counties, the selection bias in counties, and the censoring of Twitter seem also all very relevant to me, but not mentioned in the original article. Furthermore, I found the results very interesting, when you included “love”, and when you excluded “hate” from the data. In fact, it is not really convincing to exclude “love”, but exclude “hate”, as Eichstaedt et al. did in their original analysis – and I agree with you that this decision was very likely based on the results.

As you might have seen already, Eichstaedt et al. responded to your critical points in a manuscript titled “More Evidence that Twitter Language Predicts Heart Disease: A Response and Replication” which was provided as a pre-print at OSF on March 15, i.e. during the time when your manuscript was under review. I think that it would be the best if both manuscripts were published so that everyone could read them and form his/her own opinion. Thus, I do not think that you should necessarily incorporate your response to Eichstaedt et al.’s response in the current manuscript, but that it might be better to write a new response to their response (of course, only if you like) and to publish the present manuscript as it is. This would be more transparent and the discourse would be easier to follow for the scientific community.

There is only one point that I think you could add to your manuscript in response to Eichstaedt et al.’s pre-print. You write in your manuscript that Eichstaedt et al. (2015) did not provide data and script for the prediction model. Instead, you even had to reconstruct the results for the prediction model from the figures using the different colors. In the meantime – in response to your paper - Eichstaedt et al. now re-released the data on the OSF in – as they write –  more accessible form, ready for database import, and they provided in Appendix A of their response the code for the reproduction of the original findings of the prediction model.

I think that it would be good to add a footnote to your manuscript that the data and scripts for the ridge regression had been made available while the manuscript was under review, but that you did not use these data for writing your manuscript, because data and code were not available at that time. Alternatively, you could also have a closer look at the actual prediction model analysis and include this as a new section in your manuscript (but you could also leave this part for a possible response).


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: DOES TWITTER LANGUAGE RELIABLY PREDICT HEART DISEASE? A COMMENTARY ON EICHSTAEDT ET AL. (2015A)
Review round: 1
Reviewer: 4

Output:
Basic reporting: ## Note about this review

Note: The authors had released a version of this critique as a preprint on February 12th, 2018 (10.17605/OSF.IO/DURSW, version 2). The original author team of Eichstaedt et al. (which I lead; 2015) produced a substantive response which was released on March 15th, 2018 as a preprint (10.17605/OSF.IO/P75KU, version 2; Eichstaedt et al., 2018). This response also includes a detailed rebuttal of most points made by Brown and Coyle (see Appendix B). This was concluded before I accepted the invitation to serve as a reviewer (March 22nd, 2018). In agreement with the editor, I will reference this response throughout this review, as it contains a substantive (and we hope, even-handed) analysis Brown and Coyne’s critique.

Eichstaedt, J. C., Schwartz, H. A., Giorgi, S., Kern, M. L., Park, G.,... Ungar, L. H. (2018, March 15). More Evidence that Twitter Language Predicts Heart Disease: A Response and Replication. http://doi.org/10.17605/OSF.IO/P75KU. https://psyarxiv.com/p75ku/.

Fundamentally, their critique is not a reanalysis of our work, contrary to the title of the manuscript, and the claims made in the abstract. The authors’ critique does not attempt a replication of our claim, implied in their title, that county-level Twitter language predicts county-level heart disease rates.

Instead, it contains a different analysis of language correlates of county-level suicide rates, which the authors claim should match the county-level correlates of heart disease mortality. In our response (Eichstaedt et al., 2018), we found suicide rates to be are uncorrelated with heart disease rates and their linguistic correlates to mostly disappear when county elevation and rural populations are controlled for (unlike heart disease associations), suggesting that county-level suicide rates are not a straightforward measure of county-level psychological health. A CDC-reported measure of poor mental health based on phone surveys, on the other hand, shows the same pattern of correlations with psychological Twitter Language as does heart disease mortality (see Eichstaedt et al., 2018).

The manuscript would be better framed as related work, or developed into an even-handed commentary on social media-based or epidemiological methods more generally. More details are given below.

The most important limitations are flagged in the experimental designs section.

## Concerns about basic reporting -- Summary

In terms of basic reporting, I would like to see the following shortcomings addressed before a possible publication of the manuscript. (a) Claims made in Eichstaedt et al., 2015 are misrepresented; (b) the discussion of the sources of noise fails to acknowledge the principle claim of Eichstaedt et al., 2015, namely, that prediction models can use Twitter language encodings to predict heart disease mortality out-of-sample, that is, in an experimental set up in which sources of noise would work against (and not for) the ability to predict heart disease rates; (c) concerns about different kinds of noise in county-level variables and Twitter data are speculative and one-sided, lack empirical estimates, and do not properly acknowledge the large literature using these data sources.

## (a) Misrepresentations of the original article

There are a number of misrepresentations in the manuscript, which are identified in detail in Appendix B of Eichstaedt et al., 2018. The most severe ones are flagged here.

# Claims of independent psychological causation

The authors allege that:

“The principal theoretical claim of Eichstaedt et al.’s (2015a) article appears to be that the best explanation for the associations that were observed between county-level Twitter language and AHD mortality is some geographically-localized psychological factor, shared by the inhabitants of an area, that exerts a substantial influence on aspects of human life as different as vocabulary choice on social media and arterial plaque accumulation, independently of other socioeconomic and demographic factors.” (p. 26, lines 599ff)

The 2015 article did do not claim independence of psychological markers from socioeconomic and demographic factors (and the principal claim was stated in our title, “Psychological Language on Twitter Predict County-level Heart Disease Mortality”). Regarding the authors’ claim, the article stated at the end of the results section:

“Taken together, these results suggest that the AHD relevant variance in the 10 predictors overlaps with the AHD-relevant variance in the Twitter language features. Twitter language may therefore be a marker for these variables and in addition may have incremental predictive validity.” (p. 164)

The article also specifically disclaimed making causal inferences, as it was purely cross-sectional:

“Finally, associations between language and mortality do not point to causality; analyses of language on social media may complement other epidemiological methods, but the limits of causal inferences from observational studies have been repeatedly noted (e.g., Diez Roux & Mair, 2010)." (p. 166)

Please clearly state the claims made by the 2015 article throughout the manuscript – psychological markers measured through Twitter mark, and in large part overlap in variance, with classical predictors, among them predominantly income and education (see Figure 2 in Eichstaedt et al., 2015).

# Type A personality

The authors suggest in their introduction (p. 4) that the claims made in the 2015 article hinge on the empirical adequacy of Type A personality theory, and then continue to discuss the mixed findings that Type A personality theory may have received. Our 2015 article did not mention Type A personality theory – it observed a set of correlations at the community level, and, in the discussion, compared them to what has been observed at the individual level. Specifically, it referenced individual-level associations with depressed mood, anger and anxiety:

“Our findings point to a community-level psychological risk profile similar to risk profiles that have been observed at the individual level. County-level associations between AHD mortality and use of negative-emotion words (relative risk, 5  or RR, = 1.22), anger words (RR = 1.41), and anxiety words (RR = 1.11) were comparable to individual-level meta-analytic effect sizes for the association between AHD mortality and depressed mood (RR = 1.49; Rugulies, 2002), anger (RR = 1.22; Chida & Steptoe, 2009),  and anxiety (RR = 1.48; Roest, Martens, de Jonge, & Denollet, 2010).” (p. 164)

The authors should properly represent the claims made in the 2015 article (about hostility, depressed mood, anger and anxiety), and not suggest that the analysis is based on Type A personality theory, or require any specific personality theory to be correct.

# Unavailability of data

The authors claim that “However, as far as we have been able to establish, Eichstaedt et al. did not provide any of the code needed to reproduce their analyses (…)” (e.g., page 11)

The 2015 author team released both the county-level (a) Twitter language and (b) outcome data in a way that allowed people with some effort to reproduce the 2015 findings (county-level topic, dictionary, and 1-to-3-gram frequencies, see https://osf.io/rt6w2/). An early version of the code base was released on the research group’s homepage (wwbp.org) later in 2015. Since then, usability and documentation has been improved and it has been published and released open source in 2017 (Differential Language Analysis ToolKit, dlatk.wwbp.org; Schwartz et al, 2017). Additional step-by-step instructions to reproduce the original prediction accuracies can be found in Eichstaedt et al., 2018, Appendix A.

The authors should acknowledge that the code has be released publicly since the publication (in both 2015 and 2017), and that they made no attempt to contact the 2015 author team, who could have easily pointed them to these resources (as they already have to others).

## (b) Misunderstanding about the role of noise/bias in out-of-sample Evaluation

The manuscript in its current form fails to acknowledge the fact that the principal claim that Twitter language encodings can be used to predict heart disease rates are determined out-of-sample, that is, in an experimental set up in which the prediction models are only evaluated on “test” counties not used during model fit (“training”). In other words, in our work, language patterns that generalize across both training and test counties contribute to correct predictions – and sources of noise in the data would likely degrade the ability of the models to find patterns that generalize across all counties.

The current discussion of sources of error, bias and noise in the manuscript (including the unrepresentativeness of Twitter users, Twitter bots, county conditions changing over time, potential unreliability of death certificates, etc.) is framed rhetorically to suggest that the possible sources of error make our finding that Twitter predicts AHD less reliable or robust. But these sources of noise no not disagree in substance with the results presented in the 2015 article, despite a rhetorical framing to the contrary used throughout the manuscript.

Instead, the 2015 article establishes empirically how much of the variance in heart disease can be predicted *despite* all these sources of error (which are mostly acknowledged in the original manuscript). In other words, the manuscript lists possible reasons why the out-of-sample prediction accuracies reported in the 2015 article are as relatively low as they are (out of sample accuracy r = 0.42) – accounting for 17% of the variance in heart disease--but offers no substantive critique of the methods to create these predictions, nor attempts a replication.

Please properly state the effect of the possible sources of noise/bias/error in light of the out-of-sample evaluation methods used in the 2015 article, and contextualize them in light of the relatively modest claims about how much of the variance in heart disease can be predicted used Twitter language. And please remove suggestions that the 2015 original analysis either claimed or claimed “implicitly” (line 161, p. 8) that the Twitter data sources are representative.

## (c) Speculative & one-sided critiques

The authors note that there are various sources of noise in the geo-located Twitter data and the county-level outcome data. In their role as a refutation of the claims made by the 2015 article, they are insufficiently contextualized considering the out-of-sample evaluation used in the analysis (see section (b) above).

As a commentary on social-media based and spatial / epidemiological methods more generally they lack (1) empirical estimates or estimates of the relative importance in their effect on these kinds of analysis, and more importantly, (2) an even-handed treatment of the large literature that uses these kinds of data, spanning computer science, public health and epidemiology among others. This includes critiques of big data and Twitter methods that have been published previously.

# …Regarding Twitter Data

For example, as was noted in the 2015 article, users who tweet are not representatively selected, and some of the tweets (7%) are incorrectly mapped to counties. Further, some people may move from county to county, the way the “Garden Hose” Twitter sample is selected is non-random or otherwise imperfectly provided by Twitter, there are bots on Twitter, etc. These critiques are valuable, but in their current form are insufficiently integrated with the rest of the literature. A large number of publications has used geo-tagged Twitter data for all sorts of applications including health predictions—the 2015 article is far from the only article using these methods.

e.g.

Culotta, A. (2014, April). Estimating county health statistics with twitter. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 1335-1344). ACM.

Or, for critical reviews of these methods consider:

Pavalanathan, U., & Eisenstein, J. (2015). Confounds and consequences in geotagged Twitter data. arXiv preprint arXiv:1506.02275. (Published at EMNLP)

If a critical appraisal of social media-based methods is included, please provide a more balanced survey of the use and discussion of geo-tagged Twitter data in current research.

# …Regarding heart disease data

The authors doubt that the coding on death certificates for underlying cause of death is reliable (p. 13).

We agree that, like outcomes used in nearly all public health studies, there is some degree of error in the heart disease mortality rates and other outcome variables, and we noted this in the original paper. The source of mortality data we used (the mortality rates from the Centers for Disease Control and Prevention’s Wide-ranging Online Data for Epidemiologic Research database, or CDC Wonder for short) are widely used in research. Our analysis and hundreds of others do in fact depend on the assumption the main source of variance within these officially-reported data to be what they profess to measure, in the same way that these outcomes and estimations are used throughout medical and public health research.

e.g.

Pinner, R. W., Teutsch, S. M., Simonsen, L., Klug, L. A., Graber, J. M., Clarke, M. J., & Berkelman, R. L. (1996). Trends in infectious diseases mortality in the United States. JAMA, 275(3), 189-193.

Jemal, A., Ward, E., Hao, Y., & Thun, M. (2005). Trends in the leading causes of death in the United States, 1970-2002. JAMA, 294(10), 1255-1259.

Murray, C. J., Kulkarni, S. C., Michaud, C., Tomijima, N., Bulzacchelli, M. T., Iandiorio, T. J., & Ezzati, M. (2006). Eight Americas: investigating mortality disparities across races, counties, and race-counties in the United States. PLoS medicine, 3(9), e260.

Hansen, V., Oren, E., Dennis, L. K., & Brown, H. E. (2016). Infectious disease mortality trends in the United States, 1980-2014. JAMA, 316(20), 2149-2151.

In addition, the McAllum, St. George and White (2005) citation given by the authors to support the unreliability of heart disease death statistics (line 306, p. 13) is based on the qualitative output of four teleconferenced focus groups across 16 General Practitioners in New Zealand, which concludes that “Improving death certification accuracy is a complex issue.” This appears to have limited applicability to CDC-reported heart disease rates in the U.S., which the 2015 article is based on.

Please acknowledge the wide use of these data sources in health research, and if a critique of the use of such data sets in epidemiological research is intended, please provide an even-handed accounting of the reliability of these data in previous research.

## Referencing

A number of citations given throughout the article do not appear to support the claims after which they are provided (these are relatively minor points).

//

Page. 4, line 80 -- “At best, negative affectivity is likely to be no more than a non-informative risk marker (Ormel et al., 2004), not a risk factor for AHD. Its apparent predictive power is greatly diminished with better specification and measurement of confounds (Smith, 2011).”

Both of these references are about personality traits, which are not referenced in our paper.

Ormel, J., Rosmalen, J., & Farmer, A. (2004). Neuroticism: A non-informative marker of vulnerability to psychopathology. Social Psychiatry and Psychiatric Epidemiology, 39, 906–912.

Smith, T. W. (2011). Toward a more systematic, cumulative, and applicable science of personality and health: lessons from type D personality. Psychosomatic Medicine, 73, 756 528–532.

The Ormel, Rosmalen and Farmer paper critiques the idea of neuroticism (NOT negative affectivity) as being informative as an explanatory construct over and above it describing a characteristic level of distress (which it acknowledges is connected to health outcomes).

The Smith article is an editorial comment about Neuroticism and Type D Personality. The 2015 article makes no claims about personality.

//

Page 13, line 306 -- McAllum, St. George and White, 2005 – see above.

//

Page 22, line 496

“thus the statistical power to detect an effect sufficiently high, that these p values arguably constitute quite strong evidence in favor of the null hypothesis of no effect (cf. Vazire, 2017).”

While I am sympathetic to the statistical idea being conveyed here, the reference given is to a non-peer-reviewed blog post titled “be your own a**hole.”
Experimental design: ## Main Analyses

The manuscript claims to be a re-analysis of the 2015 Eichstaedt et al. paper in abstract and title. The 2015 paper had two major sections: (a) an evaluation of Twitter to cross-sectionally predict heart disease mortality, and (b) an exploration of the language correlates of heart disease mortality. This manuscript attempts a re-analysis of neither and thus its framing is inappropriate.

The main empirical contribution of the manuscript is the exploration of the Twitter language correlates of county-level suicide rates, which is not a reanalysis of the Eichstaedt et al. (2015) study. I will evaluate in this section (1) the quality of the statistical analyses, and (2) how the statistical analyses presented relate to the claims made in the article title and abstract.

Regarding (1), the reported dictionary correlations with age-adjusted suicide rates from CDC Wonder across the N = 741 counties for which sufficient data were available reported in Table 1 appear correct, and have been independently reproduced in Eichstaedt et al., 2018 (compare Table 1 in this manuscript with Table 1 in Eichstaedt et al., 2018). Given the high intercorrelations between dictionary and topic frequencies (see Table S2 in Eichstaedt et al., 2018), the topic-based findings visualized in Figure 2 also appear plausible.

However, I remain wholly unconvinced about (2), namely that the statistical analysis about suicide rates presented in the manuscript are meaningfully related to the heart disease correlations presented in the 2015 article.

Specifically, the authors connect the suicide analysis to the heart disease analysis through the following theoretical assumption: “we might expect county-level psychological factors that act directly on the health and welfare of members of the local community to be more closely reflected in the mortality statistics for suicide than those for a chronic disease such as AHD.” (page 6).

However plausible this may appear at the individual level, no empirical support is given for this critical assumption at the aggregate, county level, nor is the literature on the epidemiology of suicides properly considered.

In fact, the literature suggests suicides are a complex (and often baffling) mortality outcome that shows strong and robust links at the county level to (a) elevation (r = .51, as reported by Kim et al., 2011, and r = .50, as reported by Brenner et al., 2011) (perhaps because of the influence of hypoxia on serotonin metabolism; Bach et al., 2014) in addition to (b) living in a rural areas (e.g., see, Hirsch, 2006, for a review; Searles et al., 2014), attributed in part to social isolation and insufficient social integration, a trend that has increased over time (Singh & Siahpush, 2002; see Eichstaedt et al., 2018 for a full discussion). Implicit in these associations is also the increased availability of guns in rural communities, the preferred means of committing suicide.

In the original 2015 analysis, we tested the dictionary associations with heart disease rates using its strongest covariates as controls (income and education), finding that most of the negative language variables remained significantly associated.

In the response to this manuscript (Eichstaedt et al., 2018), we focused on an analysis of dictionary correlations for parsimony. When controlling the associations between Twitter dictionaries and suicide rates for its strongest covariates--elevation and rural population--the language correlations reported in this manuscript are no longer significant (see Eichstaedt et al., 2018, Table 1, column 2). In contrast, controlling the association between heart disease rates with Twitter dictionaries for elevation and rural population does not noticeably affect those coefficients – all significant associations remain significant (see Eichstaedt et al., 2018, Table 1, columns 3 and 4).

This suggests that the associations reported for county-level suicide rates are not robust, and likely in large part driven by county-level confounding variables.

To more directly test the authors’ hypothesis that more psychological variables ought to be better candidates for association with psychological Twitter language, we tested the most psychological variable we had released with the original 2015 paper: the number of mentally unhealthy days people reported on average in a county, based on the CDC’s Behavioral Risk Factor Surveillance System (BRFSS). Unlike suicides, mentally unhealthy days correlate with the psychological dictionaries in the same directions and roughly at the same magnitudes as heart disease mortality (see Table 2 in Eichstaedt et al, 2018).

To summarize, a) the suicide language correlations are not robust and likely associated with confounds which are well known to the suicide literature, b) a clear CDC-reported measure of county psychological health shows the same correlations as does heart disease mortality.

Thus, in my view the empirical analysis offered in this manuscript is insufficiently developed to support the claims made in the title and abstract—that is, the suicide analyses are unrelated in important ways to the heart disease mortality and unsuitable as empirical support offered in a manuscript that is framed as a “re-analysis” of the 2015 heart disease article.

As its own contribution to the literature on the epidemiology of suicide, it would require further development and integration with the existing literature.

# Spatial analyses

The authors split the U.S. into a Northern and a Southern half and report language associations to appear stronger in the North but mostly disappear in the Southern Half. This raises a pertinent research question about how psychological phenomena should be treated statistically under spatial aggregation.

Geographic psychology is a relatively new subfield within psychology, and the authors raise the question about what role specialized regression techniques from other fields (like spatial regressions from geography) may play in improving our ability to robustly relate psychological phenomena to different spaces. This analysis could be developed further, but should be clearly framed as an open research question in psychology that is relevant to most spatial analyses that span an area as wide and diverse as the U.S.
Validity of the findings: As stated in the experimental design section, the claims made in title and abstract are not supported by the suicide-related analyses in the manuscript. The conclusions drawn by the authors are not supported by the experimental design.

I see a number of directions in which this manuscript could be developed.

(a) It could be reframed as an exploration of the language correlates of suicides. In that case, the analyses need to be properly developed to incorporate what is known about county-level suicide rates. In the current form, the analyses appear insufficiently developed.

(b) The manuscript could be developed into a full commentary of social-media based and/or epidemiological methods used in psychology. In that case, an even-handed review of the associated literatures would be required (in its current form it appears one-sided and largely speculative).

(c) The analyses could be replaced with an evaluation of the correlational profiles of a wider variety of more unambiguously psychological variables and considered in light of the associated literatures. To the extent such a manuscript is still framed as a commentary on the heart disease work, a clear empirical rationale ought to be developed how the analyses relate to the heart disease results.

(d) The manuscript could attempt a replication of the results presented by Eichstaedt et al., 2015 (see Eichstaedt et al., 2018, Appendix A for step-by-step instructions) and report on it.

(e) The manuscript could explore issues of spatial aggregation of psychological phenomena.

In the current form of the manuscript, none of these issues is sufficiently developed.
Additional comments: To reiterate, this critique is ill-framed as a re-analysis of the Eichstaedt et al., 2015 article, and it does not, in fact, attempt a replication of the key claim of that article (that county-level Twitter language predicts county-level heart disease rates). Instead, it contains an exploratory analysis of language correlates of county-level suicide rates--which are (a) uncorrelated with heart disease rates and (b) disappear when county elevation and rural populations are controlled for, suggesting that county-level suicide rates are not a straightforward measure of county-level psychological health. In addition, (c) a CDC-reported measure of poor mental health based on phone surveys, on the other hand, shows the same pattern of correlations with psychological Twitter Language as does heart disease mortality.

The manuscript contains a number of speculative doubts about data and methods that do not just apply to the Eichstaedt et al., 2015 paper, but to large literatures in computer science, public health and epidemiology, which are insufficiently taken into account in this 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: DOES TWITTER LANGUAGE RELIABLY PREDICT HEART DISEASE? A COMMENTARY ON EICHSTAEDT ET AL. (2015A)
Review round: 2
Reviewer: 1

Output:
Basic reporting: The authors adequately responded to the general feedback and to my specific comments in the previous round (Review 1).

However, there seems to be a misunderstanding of the work in the comment responding to point #3 in my original review regarding misspellings. The "topics" are not manually curated by Eichstaedt et al., but are identified automatically with clustering algorithms (that's in fact a big part of the 'open vocabulary' approach they use in their work). Misspelled words are thus not misspellings on the part of Eichstaedt et al., but rather misspellings of Twitter users that were present in the data. Unless there is a misunderstanding on my part, I suggest the authors double check their understanding of how the 'topics' are interpreted, and make sure their manuscript describes them accurately.
Experimental design: The authors addressed this adequately.
Validity of the findings: The authors addressed this adequately.
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: DOES TWITTER LANGUAGE RELIABLY PREDICT HEART DISEASE? A COMMENTARY ON EICHSTAEDT ET AL. (2015A)
Review round: 2
Reviewer: 2

Output:
Basic reporting: No comment.
Experimental design: No comment.
Validity of the findings: No comment.
Additional comments: I thank you for the thorough revision and the detailed explanations in the cover letter. I have no further questions. I think that this manuscript makes an important contribution, and I am looking forward to seeing this paper being published.


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: DOES TWITTER LANGUAGE RELIABLY PREDICT HEART DISEASE? A COMMENTARY ON EICHSTAEDT ET AL. (2015A)
Review round: 2
Reviewer: 3

Output:
Basic reporting: (see attached PDF document)
Experimental design: (see attached PDF document)
Validity of the findings: (see attached PDF document)
Additional comments: (see attached PDF document)


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: HOW MUCH GENETIC VARIATION IS STORED IN THE ENDANGERED AND FRAGMENTED SHRUB TETRAENA MONGOLICA MAXIM?
Review round: 1
Reviewer: 1

Output:
Basic reporting: The manuscript is, in general, written in understandable English, but there are a number of grammatical errors which need to be made and improvements which I would like to suggest. I have indicated these errors and improvements in the general comments to Author.

The authors have used sufficient references, but they seem to have largely ignored the work of Ge et al., 2003. The aim of that study was the same as theirs, namely to assess the genetic variation in Tetraena mongolica, although different methods were used for that assessment, i.e. ISSRs. Ge et al., also come to very similar conclusions, and these are also not stated in the Introduction, nor are they discussed in the Discussion. The Conclusions that Ge et al., 2003 are furthermore also very similar, both with regard to a recent bottleneck in the population and that the populations are highly endangered. If this was the recommendation already in 2003, can the authors comment whether anything has changed? Certainly, the work done by Ge et al., 2003, must be discussed in the present publication both in the context of the similarity of their findings in spite of the use of different methods, and the consequences of their findings and whether the previous recommendations have at all been implemented, which appear not to be the case.

The article conforms to the professional article structure including figures and tables. Raw data has not been shared. Aims and objectives have been clearly stated.
Experimental design: The research described in this manuscript does conform to PeerJ's requirement of scientific and methodological soundness.

In the light of the comments made about the fact that this study has the same aims as the study of Ge et al., 2003, it is somewhat questionable whether the study is meaningful and relevant, and because the findings do not contradict the findings of Ge et al., 2003, nor do they really fill a knowledge gap, all they do is they reiterate and confirm the study of Ge et al., 2003, albeit with different experimental methods and therefore different results.

The experimental design in this study is relatively simple, i.e. sampling of extant populations and microsatellite analysis followed by the population genetic analysis based on the generated data. The methods are described in sufficient detail to allow their replication. The microsatellite analyses appear to have been correctly performed and the results have been correctly presented and interpreted.
Validity of the findings: The microsatellite results of the study are new, and the data appears to be robust and statistically sound. The results represent a replication of a previous study which analysed the same research question using different experimental methods. The conclusions are well stated and clear. The authors have not speculated beyond the limits of their data. This study is, however, not adequately discussed in the context of the previous study by Ge et al., 2003. Both studies come to the same basic conclusions.
Additional comments: The authors state that the genus is monotypic (line 62) which is incorrect . Beier et al., 2003 performed a phylogenetic analysis on a large proportion of the members of the subfamily Zygophylloideae and renamed approximately 40 species, previously placed in the genus Zygophyllum, in a broader genus Tetraena. This is the currently accepted taxonomy of the genus. The authors should correct this and reference relevant recent literature confirming this (Lauterbach et al., 2016).

On line 68, the authors state that the shrub contains triacylglycerol. Firstly, triacylglycerol should be replaced with "triacylglycerols" i.e. plural. Triacylglyerols are the chemical name for fats consisting of glycerol esterified with fatty acids of different lengths and different numbers of double bonds i.e. saturation. They are always a mixture and should be referred to in plural. A reference should be given. If this is an assumption, then I would suggest that "triacylglycerol" be replaced with "waxes and oils", as these are the most common highly combustible compounds that are found in plants.

In line 143, I would like to question the validity of the average generation time really being as low as only 4 years. These are perennial woody shrubs with long lifespans. Unless they are harvested by humans as a result of which their generation time is lowered, I would question this assumption. How did they authors who have published this, come to this conclusion? In my opinion, this should at least be critically discussed in a little more detail.

Grammatical corrections and suggested improvements:
1.	Title add "the" into the title: How much genetic variation is stored in the endangered and fragmented shrub Tetraena mongolica Maxim?
2.	Line 54, replace "Besides" with "However".
3.	Line 58, replace "Besides" with "Furthermore".
4.	Line 96, add words: "purified by using the EasyPure etc."
5.	Line 98: "genetic markers".
6.	Line 99: I question whether MgSO4 was used, was MgCl2 not rather used?
7.	Line 104: "with the GS500 marker".
8.	Line 113: replace "Besides" with "In addition".
9.	Line 168: "psendophase" should be "pseudophase".
10.	Line 177: replace "meanwhile" with "whilst" and remove comma before and after the word.
11.	Line 179: replace "disclosed" with "indicated".
12.	Line 180: insert "a" to read "passed through a significant reduction".
13.	Line 182: insert "the current" in "for the current T. mongolica population".
14.	Line 184: replace "times" with "fold".
15.	Line 186: replace "indicating" with "indicate". Also replace "in" with "approximately".
16.	Line 189: insert "a" in "has undergone a dramatic population".
17.	Line 238: correct and expand "siginificant" should read "significantly".
18.	Line 240: correct "genetics" to "genetic".
19.	Line 242: I would suggest to add "in T. mongolica" after "among extant populations".
20.	Line 250: correct sentence to read "were successfully genotyped at 12 nuclear loci".
21.	Line 255: correct sentence "which was likely to be affected by early mankind activities" to read "which was likely to be affected by recent human activities".
22.	Line 313: the author name should be written in capitals "Maxim".
23.	Line 334: capitalize journal name.
24.	Line 348: do not abbreviate journal name.
25.	Line 353: add "of the USA" to journal name.
26.	Line 361: Write species name correctly  "Adiantum capillus-veneris".
27.	Line 389: correct "Republicae".
28.	Figure 1 legend "populations".
29.	Table 2 Legends: "shrubs"


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: HOW MUCH GENETIC VARIATION IS STORED IN THE ENDANGERED AND FRAGMENTED SHRUB TETRAENA MONGOLICA MAXIM?
Review round: 1
Reviewer: 2

Output:
Basic reporting: The grammar should be checked, as there are some very long running sentences. Not all the references in the text correspond to the appropriate figure or table. Please, make sure all references are correct.
Experimental design: 1.- Field sampling and work were approved
2.- It was mentioned that the species occupies a wide area in the Gobi desert, but is it abundant? Are those 8 populations representative of the entire range? What is the entire range?
3.- The estimation of null alleles has to be mentioned in the methods
4.- l. 126 The priors in the Structure analysis are correct, but more explanation on why they were chosen would be useful.
5.- In general, please state clearly how the significance of each result was measured and that all appropriate p-values are clearly reported.
Validity of the findings: 1.- Table 3.- There are no double asterisks, please correct the legend on the table. Besides, if the comparisons are all significantly different from 0 in all pairs with asterisks, then the authors cannot argue extremely weak genetic differentiation (l. 171), as it is low, but significant in most cases. The authors mention there is no significant IBD, but refer to Fig.3, where there is no information on the tests. Please include the IBD graph, correlation coefficient and p-values for that test in the results section.
2.- There are some contradicting statements in the discussion regarding to the Structure and Fst results. Whereas there is no broad geographic pattern of population structure, the results of both analyses show that populations are differentiated due to differences in allele frequencies. A visual inspection of the raw data supports this idea, therefore one cannot just infer widespread genetic connectivity and gene flow from the results. Structure can detect very broad patterns of genetic structure, and FST is a summary statistic with limited explanatory power. Therefore, I suggest to do a multivariate analyses based on genetic covariance like the one implemented by Population Graphs (Dyer & Nason 2004). This type of graph would show which populations are indeed genetically connected to one another, and which could be vulnerable to isolation (limited number of connections).( http://dyerlab.github.io/popgraph/).
3.- As one of the aims of this work was to evaluate the effect of landscape or antropogenic barriers in the distribution of genetic variation among populations, I consider that the structure analysis without any geographic information may not be the most accurate. I suggest an analysis designed to detect genetic barriers, such as Monmonier implemented by the R-package adegenet (Jombart 2008). The results on their own do not really put to test the main premise of the effects of barriers on the genetic variation of the populations, and the significant pairwise Fst values suggest there might be genetic differentiation among different populations that is not clear in the STRUCTURE analysis.
Additional comments: The work has been through and the sampling quite impressive. I believe these types of studies are very important to evaluate the status in rapidly declining populations. However, the the analyses implemented were not the appropriate ones to detect what might be weak signals of genetic differentiation among populations.


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: HOW MUCH GENETIC VARIATION IS STORED IN THE ENDANGERED AND FRAGMENTED SHRUB TETRAENA MONGOLICA MAXIM?
Review round: 2
Reviewer: 1

Output:
Basic reporting: After the first review and the implementation of suggested changes, as well as the linguistic assistance given to improve the manuscript, it is now a lot clearer. The authors have expanded the literature references which is good. All figures and tables are correctly prepared and presented.
Experimental design: After review, the experimental design now conforms to the requirements of PeerJ.
Validity of the findings: The findings are valid, but I have my concerns that the SSR technique gives an overestimation of genetic diversity. I have therefore suggested certain additional changes to the interpretation of these data. I am also concerned that the conservation message of the findings of this study are underestimated, and the study sketches a very poor picture for the long-term survival of the species. I have therefore suggested some modifications which emphasize this more strongly. My modifications and corrections are contained in the attached file.
Additional comments: I am satisfied that the changes that I have requested have been made by the authors. However, through additional changes that the authors have made, further errors and misinterpretations have now crept in again which require corrections once again. I have made suggestions for improvements and once these have been made, the manuscript will be in a publishable form.


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: HOW MUCH GENETIC VARIATION IS STORED IN THE ENDANGERED AND FRAGMENTED SHRUB TETRAENA MONGOLICA MAXIM?
Review round: 2
Reviewer: 2

Output:
Basic reporting: The grammar was greatly improved.
Experimental design: No comment
Validity of the findings: The new analyses supported previous conclusions. There is no more to add.
Additional comments: The authors have greatly improved the manuscript and addressed all previous concerns.


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: INTERLEUKIN 35 INDUCED TH2 AND TREGS BIAS UNDER NORMAL CONDITIONS IN MICE
Review round: 1
Reviewer: 1

Output:
Basic reporting: General overview:
Author was trying to investigate the effects modulating IL-35 levels in vivo and in vitro on T cells response and also the effects on T cells subsets in normal mice.

Inappropriate usage of Wordings and phrases found throughout manuscript.

All figures and tables used are appropriate but I could not find any raw data being provided.
Experimental design: Experimental designs are considered up to date even though description on the methodology used are not very details, therefore making replications may not be possible.
Validity of the findings: All the findings are valid and would contribute to important knowledge on IL-35 research and study, but the conclusion part is a bit speculative in which authors suggested that the results indicated a strong evidence of IL-35 in immune-related disorders treatment. This cannot be so since the study was conducted in normal healthy mice. The outcome would have been different if the study is conducted in a pathologic condition in which the immune response would be more complex as compared to healthy and normal condition.
Additional comments: Comments:
1)	Overall, the manuscript was not written in good command of English therefore contributing to the lacking in the soundness of its scientific values, even though the experimental procedures used throughout the study are standard and considered up to date.
2)	There are a lot of inappropriate usage of wordings and phrases, and grammatical errors throughout the manuscript. Few examples are as follows:
•	Line 11 – “disease modelling animals” …. rather than “animal model of diseases”
•	Line 12 – the word illuminated is not the appropriate word. Perhaps “elucidated” is much more suitable.
•	Line 27 – “…..CD8+ T cells also got remarkably suppression.”…… perhaps it should read “ …. CD8+ T cells was also remarkably suppressed.”
•	Line 104 – “….mice got intravenous injected with PBS,….” ……. Perhaps should be written as “….mice received intravenous injection of PBS,….”
•	Line 145-146 – “while, the decreased CD4+CD25+ Tregs following anti-CD3/CD28 treatment received certainly amplified”…… this sentence is quite confusing.
•	Line 171 – “…..CD8+ T cells exciting, which got nice reversed in IL-35…..”…. this sentence is also quite confusing.
•	Line 209 – the word “pressed” …. Does the author mean “suppressed”?

3)	In section 2.3, the lymphocytes used were from the spleen tissues of mice, but recombinant human IL-35 was used to induce the cells. Please provide evidence that human IL-35 does work in mice cells.

4)	Section 2.9, ANOVA analysis is normally followed by a single post hoc test to confirm the significance. Any post hoc test used here?

5)	Line 232 – “….provided strong evidence of its efficacy in immune-related disorders treatment”….. this statement is a bit inappropriate at this stage since the study was conducted in normal healthy mice and not in any pathologic condition. Efficacy of any treatment can only be assessed based on its ability to succesfully cure or at least reduce certain disease state. Since the study was conducted in normal healthy mice, there is always the possibility that the outcome of the study would be different in pathologic condition in which a complex immune response may occur with the release of many important mediators as compared to basic immune response in healthy animals.


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: INTERLEUKIN 35 INDUCED TH2 AND TREGS BIAS UNDER NORMAL CONDITIONS IN MICE
Review round: 1
Reviewer: 2

Output:
Basic reporting: -Excellent background but remove reference in(in revision) as this work is still not published or what?
-The English needs some attention. The manuscript need to be revised by a native speaker.
-Manuscript structure is good but gel figs are bad, other figures and tables are relevant and appropriate.
Experimental design: -The basic structure and conclusions are novel. Actually this topic is important
-Research question well defined, relevant & meaningful.
-investigation performed to a high technical & ethical standard
-Methods described with sufficient details.
Validity of the findings: -Conclusive results
-Data is robust, statistically sound, & controlled

-Conclusion are well stated, linked to original research question & limited to supporting results.
Additional comments: The most important point for the present study in discussion; ‘What is the difference of the present study from the others?’The present discussion section should be rewritten


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: INTERLEUKIN 35 INDUCED TH2 AND TREGS BIAS UNDER NORMAL CONDITIONS IN MICE
Review round: 2
Reviewer: 1

Output:
Basic reporting: No comment
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: PLANT DOMINANCE IN A SUBALPINE MONTANE MEADOW: BIOTIC VS. ABIOTIC CONTROLS OF SUBORDINATE DIVERSITY WITHIN AND ACROSS SITES
Review round: 1
Reviewer: 1

Output:
Basic reporting: The manuscript is well-written and well-structured. I found that the literature related to how dominant species do or do not control subordinate species composition, abundance or presence was very limited in the introduction even though this is one of the tested hypothesis in this manuscript (see for example, Garbin et al. 2016 PPEES, Gibson et al. 2012 Oikos, Grman and Suding 2010 Rest. Ecol.)
Experimental design: The research fits well with the scope of PEERJ and working hypothesis and questions are well defined in the introduction. The observational study design is however unclear. I understand that 2 meadow sites where chosen,  one site with dominance of Festuca, one site with dominance of Potentilla and one site with co-dominance between both species. Then 9 plots of 1 m2 are placed in each site using 3 transects per site with 3 plots per transect. However I don't understand (line 150-153) why among each transect inside each site, there is one plot with Potentilla dominated, one plot with Festuca dominated and one co-dominated. Is dominance (Festuca or Potentilla) determined along the three meadow site? or within each site? It is very quite confusing.

There is a lack of explanation about how you define dominant and subordinate species. When reading the text, it seems that subordinate species are all species that are not Festuca or Potentilla (and there are no transients) - graph suggests the same. Then looking at Appendix Table 1, it seems that that you also classified species based on my paper (Mariotte 2014) but it is not mentioned in the text. Appendix Table 1 shows only one species dataset but you used 3 meadow sites, are species the same in the three sites? I think that the species selection and design should be more detailed/explained because it is very confusing in the current version of the manuscript.

In term of results, I would suggest to better use the data (abiotic factors) of light availability, temperature, Soil N availability etc, maybe in a RDA of the subordinate species composition constrained by dominance type (Festuca, Potentilla, Co-dom) and all these abiotic factors you measured. An option would be to transform the treatment (dominated, removal, control) into a continuous variable (relative abundance of Festuca and relative abundance of Potentilla that the RDA could be constrained by in addition to all abiotic factors. Might be better than Table 5 and 6 but just a suggestion.
Validity of the findings: Overall the discussion and conclusion are well-written and sound but this can only be adequately judged after some clarifications are made to the method section (see my previous comments).

I would tone down the idea that subordinate species diversity and abundance patterns are not controlled by biotic factors but rather by abiotic factors because you forgot about biotic interactions with soil organisms (fungi, AMF, earthworms) which has already been shown to strongly impact the growth, drought resistance, and composition of subordinate species (Mariotte et al. 2015 Func Ecol, Mariotte et al. 2016 SBB, Mariotte et al. 2017 J Ecol). It is worth discussing this topic in addition to the role of abiotic factors.
Additional comments: Overall, I obviously like the idea of the manuscript which is in line with my own research during the past 10 years. I would recommend to clarify the method section about the plant species selection and the observational study, and also take into account of my other suggestions.


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: PLANT DOMINANCE IN A SUBALPINE MONTANE MEADOW: BIOTIC VS. ABIOTIC CONTROLS OF SUBORDINATE DIVERSITY WITHIN AND ACROSS SITES
Review round: 1
Reviewer: 2

Output:
Basic reporting: English and writing style in this manuscript need to be improved. Many mistakes in the text. (see my specific comments below)
Literature references of this manuscript are not sufficient. There are many removal studies that can provide possible explanations for the observed patterns, while the authors only referred to about five studies.
Lacks a figure or table for the results of functional trait measurements. Table 1 ang Fig. 1, Table 3 and Fig. 3 can be combined to make the manuscript more concise. Legends of the figures should be more explicit.
Experimental design: Research questions are not well defined. In the introduction the authors did not provide solid background why plant functional traits are relevant in this study. The author only measured two traits, SLA and SRL, which I think is not enough to cover the trait diversity for a meadow ecosystem, unless the authors can provide evidence that in this specific ecosystem the two traits are the main source of trait variation. In addition, the authors only measured the traits in the observational study only for the two dominant species. As the focus of this manuscript seems to be on subordinate species, I do not see the logic for not measuring traits of subordinate species. Also, the authors only reported cover/abundance data for subordinate species, but I think the abundance of dominate species is also important to consider, as removal of one co-dominant species may cause over-production of another co-dominant species rather than subordinate species. Also, in the co-dominance plots, sub-ordinate species probably also suffered from the overall dominance by the two species.
The study sites selected, and the methods used are not sufficiently described.
Validity of the findings: Conclusions are not well supported by available results. The authors claim that subordinate species diversity and composition were likely driven by abiotic factors rather than biotic interactions, however, in the results subordinate diversity and composition were significantly different among communities with different dominant species, suggesting that dominant species had large effects on subordinate species, either directly through competition or indirectly through changes in abiotic conditions. The authors did not provide information about species pools at the study site for these different communities, and measurements on abiotic factors, plant traits and plant interactions are limited, making it hard to attribute the observed patterns to any factors.
Additional comments: Specific comments
The title is too large and vague. When I first saw this title I was imagining a study based on global data.
The introduction is too long and some parts are redundant. The logic of the introduction is not very clear. It is good to introduce the importance of subordinate species in the first paragraph but it is too long as it is now. The second paragraph introducing plant functional traits is very abrupt, and there is no connection with the first paragraph. Of course functional traits of dominant species can influence performance of subordinate species, but why can they indicate species abundance and diversity? The third paragraph can be shortened too. In addition, hypothesis 1 and 3 are the same: dominant species alter subordinate diversity and composition, so they vary along a plant dominance gradient.
L63: remove ‘In fact’. It is a hypothesis, not a fact.
L73: what does ‘which’ refer to?
L81–84: maybe just simply say that environmental conditions can shape community structure.
L85: ‘trait attributes’ to ‘traits’
L86: add references.
L89–91: it is repetition to the last sentence of the first paragraph.
L95: add references.
L100–101: why quote marks for aboveground and belowground?
L110: remove ‘For example’
L114: ‘to influence’ to ‘on’
L132: what period are the mean temperature and precipitation for?
L143: add the criteria for the selection of different site type. For example, based on relative coverage of the two dominant species?
L148: do the authors mean beginning of June to late July?
L150–153: this sentence is very confusing. Earlier in this paragraph it is introduced that each site had 3 transects, so 9 transects in all. However here as I understand each transect passed through all 3 sites. Please clarify.
L160: how frequently or how many times were the plants removed?
L164: add ‘the’ in front of ‘three sites’
L164–165: remove ‘(ranging in …)’
L167–168, 184: how was percent coverage recorded? Please introduce briefly the methods of Cornelissen et al (2003)
L175: how large was the soil core?
L188: what does ‘S’ refer to in the formula?
L191: when were the microclimate measurement made? Were the values three year average?
L198: was the PAR measurement made below the dominant canopy?
L204: when were the resin bags harvested and how long had they been in the soil?
L212, 215: it may be confusing to use ‘fixed effect’ here, as readers may think there are random effects too.
L229: ‘PCO’ to ‘PCoA’
L231: remove one ‘a’
L242: ‘similarly’ to ‘similar’
L247: ‘dominated sites’ to ‘sites dominated’
L247–251: maybe move to discussion
L264–265: if I understand right, it should be ‘… greater in Festuca dominated and co-dominated than in Potentilla …’
L275, 277: should be ‘the removal of neither dominant species’
L307–308: remove ‘manipulated to become’, as this is about the observational study and it was not manipulated
L319: add references
L349: remove ‘as expected’. If that dominant species does not affect subordinate diversity was what you prior expectation, why would you do this experiment?
L387: ‘low resistance’ should be ‘high resistance’
Table 1 and 3: does alpha diversity refer to species richness?
Table 5: why are some SEs larger than means, which suggests there are negative values?
Fig 1–4: please clarify in the legends whether they are Potentilla/Festuca dominated or removal.


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: PLANT DOMINANCE IN A SUBALPINE MONTANE MEADOW: BIOTIC VS. ABIOTIC CONTROLS OF SUBORDINATE DIVERSITY WITHIN AND ACROSS SITES
Review round: 2
Reviewer: 1

Output:
Basic reporting: In figure 2 I believe that the legend in graph (D) should be Potentilla removal, Festuca removal and No removal (instead of 'Potentilla', 'Festuca', 'Co-dominated'). Also it would be worth citing separately graph (A) (B) (C) (D) (E) (F) separately in the text instead of just 'Figure 2'.

In figures 1 and 2, it would help to write '(Observation Study)' after ...plant dominance gradient and '(Experimental Study)' after ...subordinate diversity and composition, respectively.
Experimental design: Good
Validity of the findings: Good
Additional comments: Thank you very much, you adequately answered my questions and integrated my comments and I am happy with the revised version. I can be published after minor changes indicated above are taken care of. It is nice to see more experiments on subordinate versus dominant species in grasslands and the interest in this topic.


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: IMPROVING REMOTE ESTIMATION OF WINTER CROPS GROSS ECOSYSTEM PRODUCTION BY INCLUSION OF LEAF AREA INDEX IN A SPECTRAL MODEL
Review round: 1
Reviewer: 1

Output:
Basic reporting: 1.There are most of redundancy contents in discussion section, please reframe the structure and contents of this part (e.g., Line316-345 these contents should appear in the introduction). Meanwhile, authors should discuss the method and analyze specificly why the method you used underestimates GEPd of winter crops and overestimates GEPd of spring crops?

2.L393: using Table4 instead of Table3

3.Figure 2: It is not explicit about the image information. What do triangles, circles and A~E represent, respectively?

4.Figure 6: Why the value of NDVI*LAI for winter rye is higher than GEP at vegetative stage, what about other years? Is it the reason why the coefficient of determination is so low (r2=0.01) in figure 7 (A)?
Experimental design: 1. Why EVI is not used and tested but the precursor SAVI is used?

2. Line 203: How did you calculate NDVI? Provide a formula.
Compared with NDVI, EVI is widely used in various models of Gross Ecosystem Production and shows to be sensitive to vegetation growth, why not consider this vegetation indices? If is the method limitation of multispectral radiometers (Line 347-348), why not use remote sensing data?

3. Line207-215: It is not clear how the regression was done? Did you assume that the models output should be equal to the total GEP from measure data and then used this information to calculate variable a and b? If this is the case, how was the data divided between calibration and validation? Maybe you need to add more experimental data.

4. Should the model be calibrated and validated separately by including all crop-combined dataset? There are also problems with the structure of the latter part of article and amount of crop-combined dataset are not enough at daily scale.
Validity of the findings: 1. Line153-154 & Line191-192: how did authors acquired the daily data? Please explain more. The data used in all methods are obtained by authors under ideal experiment conditions (Sunny day). Can these methods be applied to in situ measurement data?

2. L373-375: All measurements were taken over the sunny days in this research, so how did you explain the weak correlation between PAR and GEP is caused by long time scales?

3. For all figures, scatter plots data for each crop at daily scale are not enough (less than the amounts of 3 years). Please check your data.
Additional comments: The authors considered the hysteresis of relationship between vegetation index and GEP and propose methods to increase modeling accuracy of daily GEP. The authors intended to propose a general model, but from the results, the general model does not seem working well. I suggest major revisions with specific 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: IMPROVING REMOTE ESTIMATION OF WINTER CROPS GROSS ECOSYSTEM PRODUCTION BY INCLUSION OF LEAF AREA INDEX IN A SPECTRAL MODEL
Review round: 1
Reviewer: 2

Output:
Basic reporting: Some English editing is required.
Experimental design: The research question is not clearly defined, but only ambiguously implied.
Validity of the findings: No comments. Please see the general comments to the authors.
Additional comments: The study aims to estimate GEP from VI and LAI, which could be retrieved from remote sensing approaches, and suggests that for winter crops, the product of VI and LAI estimates GEP better than VI alone, due to reduced hysteresis of the relationship between GEP and VI. In general, this study provides a feasible approach for routinely estimating GEP of some particular field plots, which could be used for other similar scenarios. So, I recommend this paper be published—when the following concerns and comments are addressed by the authors.

Line 18: the title is kind of too long and can be condensed.
Line 30: “vegetative stage”—this is a little ambiguous.
Line 38: what is “crop-combined dataset?” Please rephrase.
Line 41: it’s counter-intuitive that greenness index saturate in the early growing season.
Line 78: “remote estimate of LAI” – please rephrase.
Line 106: if this model is empirical, can this model be applied to other vegetation types or to same vegetation types in other regions? It would be good if the authors could address this apparent concern in the paper.
Line 147: “flow rate of 0.7 liters” → maybe the unit is not correct?
Line 151: “sunny and cloudless days” → this is repetitive.
Line 239: “dependently on the …” → depending on the…
Line 295: any potential reason for the divergent cases?
Line 373-374: could it be that all the measurements were made on sunny days, so PAR is not a limiting factor for GEP, and hence there is no relationship between PAR and GEP?
Line 384-385: This seems the main purpose of this study. Maybe the authors should state it in the abstract as well as conclusion parts.
Line 467： “what is more” → moreover.
Line 479-480: the statement about satellite remote sensing retrievals of LAI is not accurate.


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: IMPROVING REMOTE ESTIMATION OF WINTER CROPS GROSS ECOSYSTEM PRODUCTION BY INCLUSION OF LEAF AREA INDEX IN A SPECTRAL MODEL
Review round: 2
Reviewer: 1

Output:
Basic reporting: Clear and unambiguous
Experimental design: Research question is well defined
Validity of the findings: Data is statistically sound
Additional comments: The author has addressed the questions appropriately. I do not have further comments except that I feel the title is too long. It is best for the author to revise the title to be more concise.


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: IMPROVING REMOTE ESTIMATION OF WINTER CROPS GROSS ECOSYSTEM PRODUCTION BY INCLUSION OF LEAF AREA INDEX IN A SPECTRAL MODEL
Review round: 2
Reviewer: 2

Output:
Basic reporting: The manuscript has improved significantly after the revision.
Experimental design: The experimental design has improved significantly after the revision.
Validity of the findings: The manuscript has improved significantly after the revision.
Additional comments: The manuscript has improved significantly after the revision, and I recommend this paper be published.


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: GENOMIC ORGANIZATION, GENE EXPRESSION AND ACTIVITY PROFILE OF MARINOBACTER HYDROCARBONOCLASTICUS DENITRIFICATION ENZYMES
Review round: 1
Reviewer: 1

Output:
Basic reporting: The text is in general well written, although it may be improved, as some parts of the text is hard to understand.

In Introduction, there are some parts that can be deleted and others that can be expanded. Some references can be added or be upto date.

Raw data have to include all data from replicates, not only one.

The authors did not respect the format for the Abstract as defined in the Author guides, as well as the interlined spaces (should have been 2 line space).

Some figures can be deleted or moved in the Supplemental data

See my comments in the Report document
Experimental design: Most of comments related to this criterion are included in my Report document. In general, this criterion is partially covered.
Validity of the findings: Most of comments related to this criterion are included in my Report document. In general, this criterion is partially covered
Additional comments: My general and specific comments are provided in an attached document


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: GENOMIC ORGANIZATION, GENE EXPRESSION AND ACTIVITY PROFILE OF MARINOBACTER HYDROCARBONOCLASTICUS DENITRIFICATION ENZYMES
Review round: 1
Reviewer: 2

Output:
Basic reporting: The paper is too long and could be significantly shortened.
Experimental design: No comment.
Validity of the findings: No comment.
Additional comments: In this paper, the authors interrogate the genome of Marinobacter hydrocarbonoclasticus to draw conclusions about the biochemical apparatus for denitrification, and the regulation of the corresponding genes.  Perhaps most interesting is the coding potential for a Q-type NO reductase, though the authors' data suggest that only the C-type enzyme is expressed and active under the growth conditions that they use.

The organism grows rapidly by denitrification and qRT-PCR data show essentially simultaneous expression of the denitrification genes during the rapid phase of growth.  Bioreactor cultures show a second phase of slower growth, it is less clear what is going on physiologically during this second phase.

From the presence of regulatory genes and putative cis-acting regulatory sequences the authors infer a likely regulatory network governing the expression of the denitrification genes.  There are no major surprises here and regulation seems to follow the same general patterns found in other organisms (that is, with major roles for FNR- and NarXL-type regulators).

Specific comments

1.	Lines 366-368.   Here the authors are comparing distance from the start codon to distance from the transcription start site, which does not really make sense.  Distance from the start codon is not a very useful parameter.

2.	Lines 377 and 379.  Here distances from the transcription start site are given, but I think the authors mean distances from the start codon (according to the Figure).

3.	Lines 401-403.  This may just reflect differences in absolute promoter strength rather than regulatory mechanisms.

4.	Lines 425 and 436.  I would avoid mentions of death phase since viable counts have not been measured.  Dead cells contribute to optical density.

5.	Lines 514-521.  Some literature citations are needed in this passage.

6.	There is scope to shorten the paper, for example by avoiding repetition.  Some observations are repeated in the results, discussion and conclusions.


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: GENOMIC ORGANIZATION, GENE EXPRESSION AND ACTIVITY PROFILE OF MARINOBACTER HYDROCARBONOCLASTICUS DENITRIFICATION ENZYMES
Review round: 2
Reviewer: 1

Output:
Basic reporting: Clear and unambiguous, professional English used throughout.
OK

Literature references, sufficient field background/context provided.
OK

Professional article structure, figs, tables. Raw data shared.
OK

Self-contained with relevant results to hypotheses.
OK
Experimental design: Original primary research within Aims and Scope of the journal.
OK

Research question well defined, relevant & meaningful. It is stated how research fills an identified knowledge gap.
OK

Rigorous investigation performed to a high technical & ethical standard.
OK

Methods described with sufficient detail & information to replicate.
See the attachment
Validity of the findings: Data is robust, statistically sound, & controlled.
Not perfect, but satisfactory


Conclusion are well stated, linked to original research question & limited to supporting results.
OK

Speculation is welcome, but should be identified as such.
OK
Additional comments: See the attached doument


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: CHARACTERIZATION OF RETINAL REGENERATION IN ADULT ZEBRAFISH FOLLOWING MULTIPLE ROUNDS OF PHOTOTOXIC LESION
Review round: 1
Reviewer: 1

Output:
Basic reporting: This study by Ranski et al. compares photoreceptor regeneration and Muller glial activation in zebrafish retinas subjected to one versus six rounds of acute light damage and regeneration. Although studies have been done to determine the regenerative ability of the zebrafish fin after repeated rounds of injury, this has not been examined for zebrafish retina. Therefore, these data are of interest to the field. The study is straightforward, the methods and results are mostly clearly explained, and the conclusions seem reasonable. To me, the most interesting result is that repeated rounds of light damage appear to have a destabilizing effect in the retina, although the authors do not highlight this. I have only a few minor suggestions to improve the manuscript.

Introduction, line 57: in comparing mechanisms of regeneration of various tissues such as the heart, retina, and the fin in the zebrafish, the authors state that there are “resident cells in each tissue that have the capacity to act as stem cells…” In fact, it is my understanding that in the fin, several studies have shown that regeneration does not result from activation of a resident stem cell, but rather from the dedifferentiation of mature (non-dividng) cells, each of which are lineage restricted (i.e., osteoblasts only regenerate bone, dermal fibroblasts only regenerate epidermis, and so on). This is clearly not the same mechanism as is described for retinal regeneration in zebrafish. The authors should therefore take care not to over-generalize about mechanisms of regeneration across tissue types.

Introduction, lines 75-80: the authors again attempt to ascribe parallel mechanisms of regeneration in the retina, heart, and fin by suggesting that following injury each tissue participates in the initial formation of a scar, followed by scar regression and then cell proliferation/differentiation. However, this is also an over-generalization. In heart and skin regeneration-associated scarring occurs via fibroblast recruitment and deposition of cartilage. However, in retinal damage any scarring would be formed by the Muller glia themselves. Although zebrafish Muller glia undergo reactive gliosis in response to retinal damage, they do not produce a scar prior to initiating regeneration. This difference with heart and fin could be related to different regenerative mechanisms needed for neural as opposed to non-neural tissue. In any case, care should be taken not to draw unsupported parallels here.

Introduction, lines 96-99: “We found that a different subset of Müller glia reentered the cell cycle during the second round of regeneration…” These experiments are not described in the Results, although that is a very interesting finding!

There are several typos throughout the manuscript; the corrections are listed below:

The title should read “Characterization of retinal regeneration in adult zebrafish following multiple rounds of degeneration and regeneration”

Abstract, line 36: “suggests that all vertebrate Müller glia have the potential to act as…”

Abstract, line 40: “We observed that Müller glia to re-entered the cell cycle…”

Abstract, line 47: “Finally, we following the sixth round of regeneration, we…”

Introduction, line 74: “photoreceptor ablation by intense light…”

Introduction, line 94 (and elsewhere): I suggest using the phrase “dark-adapted” instead of “dark-treated”

Discussion, line 316: “Overall, our findings results demonstrate that zebrafish can regenerate…”

All figures: “immunolabeled by…” should be anti-rhodopsin, anti-UV opsin, anti-blue opsin, anti-PCNA, etc. (except for monoclonal antibodies with their own names, such as Zpr-1, 4C4, etc.).

All Figure legends: what length does the scale bar represent?
Experimental design: Materials and Methods, Photoreceptor Lesions: Please include information on how many fish were in each group, and how many biological replicates were performed for each light damage experiment (1x vs. 6x)

Results, lines 190-193 and Figure 1: The authors state that there was no difference in the number of regenerated rod photoreceptors after either 1 or 6 rounds of light damage, but no quantification is provided. Please include these data. Also, in the schematic at the top of Figure 1, shouldn’t the text in between the two timelines read “5 additional rounds”?
Validity of the findings: Figure 1: The DAPI staining at 6x compared to 1x rounds reveals a fair amount of disorganization in the ONL with a suggestion of incipient rosettes, indicating that repeated rounds of light damage is destabilizing the retina (consistent with the persistent activation of the Muller glia shown in Fig. 3). It would be nice if the authors commented on this in the results and discussion.

Results, lines 198-202 and Figure 2: Why is there so much residual rhodopsin staining at 36 hpL in the 1x image? Shouldn't these cells be almost completely ablated in the dorsal retina? The presence of additional 4C4+ microglia in the 6x retina is also interesting: are these "extra" microglia that continue to hang around between the multiple rounds of light damage, or do they go away and re-appear in greater numbers each time? Please comment on this (or if you have IHC data on 4C4 at 28 dpL please show that). Also, there is again no quantification shown (or provided in the dataset) for the rods.

Results, lines 214-215 and Figure 4: Looking at the extent of the GFAP-labeled Muller glia processes in panels 4B-4B”, is appears that the 6x regenerated retinas are thicker than 1x. Is this the case? If so, does this suggest an accumulated effect of over-proliferation with each round of regeneration?

Discussion, lines 257-266: Another possible explanation for the results is that each round of degeneration/regeneration weakens or destabilizes the retina a little more, lowering the resistance to subsequent injury (and thus undergoing more damage). This might be indicated by the persistently activated Muller glia, the disorganized appearance of the ONL, and the increased number of 4C4+ cells in the 6x retina.

Discussion, line 282: As stated above for the Introduction, I don’t think it is accurate to term this a “scar-like response”

Discussion: the authors should comment on the apparent discrepancy between the reduction in gfap mRNA expression and the increased GFAP protein in 6x retinas. What is known about the post-transcriptional regulation of GFAP expression?
Additional comments: Please see attached review


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

Input:
Title: CHARACTERIZATION OF RETINAL REGENERATION IN ADULT ZEBRAFISH FOLLOWING MULTIPLE ROUNDS OF PHOTOTOXIC LESION
Review round: 1
Reviewer: 2

Output:
Basic reporting: This is a great study to add to our understanding of the extent to which zebrafish can regenerate neurons. It is a clearly written manuscript with a coherent story provided about the ability of adult zebrafish to regenerate retinal neurons after multiple rounds of injury.

Some of the introduction material could be reorganized to make the comparison between regeneration in different tissues and the retina more apparent. For example, a previous paper (Qin et al, 2009, PNAS) showed that mps1 is needed in retinal regeneration, and that there may shared mechanisms of epigenetic regulation with the fin. This would be a good reference to include in the introduction section.

The authors should consider stating a clear hypothesis at the close of the introduction section. Based on the introduction, I would presume that the study was aimed at determining if there is a scarring reaction that is then mitigated during regeneration similar to other tissues, but that is not clearly state. Additionally, the assertion at the end of the introduction that different subsets of Müller glial cells reenter the cell cycle was not apparent in the results presented in the manuscript.

The figures are all directly relevant to the goal of the study. Figure 4C might be easier to interpret for the reader if the genes were grouped to reflect the results text and discussion. For example, a graph with proliferation-related genes and a graph of intermediate filaments, etc., or alternatively group them within one graph. This would make interpreting the data more straightforward. The figure legends should be reworded to be clear that cells aren’t labeled with a protein, but rather with an antibody. (I.e. “Rod photoreceptor outer segments are immunolabeled with anti-rhodopsin” instead of “…with rhodopsin”.)

The statistics reported on line 193 do not have any matching quantitative data, so this should be resolved.

There are some language conventions that make the manuscript feel a bit disjointed as a whole. For example, in the long second paragraph of the introduction there is a string of sentences that all begin with single transition words that feels very redundant. In lines 285-287, the pronoun reference for ‘this’ is confusing.

The authors refer to “Müller cell disorganization”. It also appears that lamination of the retina is disturbed at 36 and 72 hours post light onset in the 6x treatment, possibly also with a reduction in the number nuclei in the outer nuclear layer. Is this consistent across biological replicates observed or just appears so in the images in the figures?
Experimental design: More detail on the immunofluorescence analysis should be included. In particular: 1. Include the number of biological replicates that were examined per treatment and timepoint, and 2. State whether the data presenting average number of cells was over a particular linear distance (figs 2K and 5E).

Because the immunofluorescence was not done in a quantitative manner, I suggest the authors be cautious in making assertions about the relative levels of expression of proteins. If, however, images were taken in such a way to ensure valid comparisons of the level of fluorescence across groups, then these methods should be clearly described. For example in Figure 3 A-B, one could argue that the GFAP might just be redistributed in the 6x treatment, as the end feet of the Müller glia in the 6x treatment, particularly at the apical side, appear to have lower GFAP amounts relative to the 1x treatment.

Was retinal tissue used for qRT-PCR put directly into Trizol when dissected or frozen for storage (or other)?
Validity of the findings: In general, I think the Discussion section could be much stronger and better serve the findings of this study. It is not clear how the proposed explanations in the first paragraph of the discussion were developed. If there are references to support these hypotheses, they should be included. The discussion should better reflect the Introduction that set up the idea that regenerative responses start with a scarring response, and later the scar is replaced by regenerated tissue. The authors provide clear evidence that there is a much stronger gliotic response from Müller glia in the 6x treatment and that at 28 days post light onset the retinal structure appears normal. This would fit quite well with the information in the Introduction. The final closing paragraph should better state the benefit this study provides to the field.
Additional comments: This is a great study that many will find interesting and valuable. With minor revisions to the text and clarification on some of the methods, the presentation of the data will be even more impactful.