First, we producecausal estimates of the elasticities between biodiversity outcomes and air pollution. We use aresearch design that isolates variation in local pollution driven by transported pollution fromdistant, upwind cities (e.g., Deryugina et al., 2019; Anderson, 2020). We show that “upwindpollution” coming from areas over 300 km away generates substantial variation in local airquality, and these imported pollution shocks cause reductions in local biodiversity outcomes.Second, we estimate the impact of the military spending shocks on air pollution, and multiplythese estimates by the biodiversity-pollution elasticities we obtain from step one. Together,these exercises give us the expected impact of the military shocks on biodiversity throughair pollution. We find that pollution accounts for 20-60 percent of the reduced form effect ofmilitary shocks, suggesting air pollution is a first-order pathway underlying the production-biodiversity link

Please note, not all rigor criteria are appropriate for all manuscripts.

ScreenIT Sep 27, 2021 SciScore for 10.1101/2021.09.22.461342: (What is this?)Please note, not all rigor criteria are appropriate for all manuscripts.

Is the study design appropriate and are the methods used valid? Yes

Some details of the methods are lacking. For example, the MUpro provides two methods, it is necessary to specify which method was used in the analysis. The confidence score of each prediction should also be provided. Besides, some results from I-Mutant and MUpro were conflicting, the authors may want to discuss the discrepancy.

Discussion, revision and decision Discussion and Revision Author response We would like to thank the reviewers for their valuable comments. Below we provide pointwise response and the changes made in the revised manuscript. To Dr. Jyotsnamayee Sabat

PeerRef Dec 15, 2021 Discussion, revision and decision

Author response

Nov 26, 2021 Peer review report Reviewer: Hurng-Yi Wang Institution: Institute of Ecology and Evolutionary Biology, National Taiwan University email: hurngyi@gmail.com Section 1 – Serious concerns Do you have any serious concerns about the manuscript such as fraud, plagiarism, unethical or unsafe practices? No Have authors’ provided the necessary ethics approval (from authors’ institution or an ethics committee)? not applicable Section 2 – Language quality How would you rate the English language quality? Medium quality Section 3 – validity and reproducibility Does the work cite relevant and sufficient literature? No Is the study design appropriate and are the methods used valid? No Are the methods documented and analysis provided so that the study can be replicated? Yes Is the source data that underlies the result available so that the study can be … More Peer review report Reviewer: Hurng-Yi Wang Institution: Institute of Ecology and Evolutionary Biology, National Taiwan University email: hurngyi@gmail.com

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Pt-12:

The “Analysis of the Mutational Profile of Indian Isolates” should be moved to Materials and Methods.

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Article activity feed Version 2 published on bioRxiv

AgarwalNita Parekh

Abstract

In this study we carried out the early distribution of clades and subclades state-wise based on shared mutations in Indian SARS-CoV-2 isolates collected (27 th Jan – 27 th May 2020). Phylogenetic analysis of these isolates indicates multiple independent sources of introduction of the virus in the country, while principal component analysis revealed some state-specific clusters. It is observed that clade 20A defining mutations C241T (ORF1ab: 5’ UTR), C3037T (ORF1ab: F924F), C14408T (ORF1ab: P4715L), and A23403G (S: D614G) are predominant in Indian isolates during this period. Higher number of coronavirus cases were observed in certain states, viz ., Delhi, Tamil Nadu, and Telangana. Genetic analysis of isolates from these states revealed a cluster with shared mutations, C6312A (ORF1ab: T2016K), C13730T (ORF1ab: A4489V), C23929T, and C28311T (N: P13L). Analysis of region-specific shared mutations carried out to understand the large number of deaths in Gujarat and Maharashtra identified shared mutations defining subclade, I/GJ-20A (C18877T, C22444T, G25563T (ORF3a: H57Q), C26735T, C28854T (N: S194L), C2836T) in Gujarat and two sets of co-occurring mutations C313T, C5700A (ORF1ab: A1812D) and A29827T, G29830T in Maharashtra. From the genetic analysis of mutation spectra of Indian isolates, the insights gained in its transmission, geographic distribution, containment, and impact are discussed.

Pt-13: I want to know how the representative sequences were selected for different states. Is it based on no. of sequences submitted or positivity rate of a particular region? All the Indian isolates available in GISAID for the period 27th Jan – 27th May 2020 were download and considered for analysis. NO state-wise selection was done.

Demographic Analysis of Mutations in Indian SARS-CoV-2 Isolates

The first intervention, surgical treatment, can’t even be seen on this scale, because it has such a small impact relative to other interventions. And the best strategy, educating high-risk groups, is estimated to be 1,400 times better than that. (It’s possible that these estimates might be inaccurate, or might not capture all of the relevant effects. But it seems likely that there are still big differences between interventions.)