Meteorological and Water Quality Factors Associated with Microbial Diversity in Coastal Water from Intensified Oyster Production Areas of Thailand

Round 1

Reviewer 1 Report

This study focused on the distribution of bacterial pathogens including fecal coliforms, Escherichia coli, Vibrio. parahaemolyticus., Vibrio. Cholerae., and Salmonella, as well as the association between the levels of E. coli and V. parahaemolyticus with meteorological factors and microbial diversity in seawater from oyster cultivation field of Thailand coastal area. Although some results could attract the interests of a specialized scientific readership, in my opinion, this study is too descriptive and flawed in most of its sections.

 1. The aims and motivations are vague and explicitly descriptive of a local setting only (see L59-63, L68-72). More details are required on specific objectives. Microbial contamination in the marine environment and seafood safety (e.g., shellfish) was extensively investigated in numerous different aquacultural fields. Therefore, it is crucial to be more specific and convincing on the contributions that this study could provide to the existing knowledge. By reading the introduction, the study is not likely driven by clear (and novel) research hypotheses, and ambiguous statements are spread through the text. The authors paid a lot attention to introduce the global and regional seafood yields and how important of shellfish production to Thailand (see L 32-46), that’s not necessary and will distract the readership from your main idea. The title of this manuscript focused on the associations between meteorological factors and microbial diversity, however, from what I read, the authors didn’t introduce any of relevant background knowledge. Please, re-organize about the research background information and hypotheses to be coherently presented in the introduction section.

 2. I have major concerns regarding the representativeness of water samples collected from 0.3-0.5 m below the seawater surface, which may not be able to sufficiently represent the real condition of oyster living depth considering the marine environment heterogeneity.

 3. The authors ignored the collinearity of environmental variables themselves when using the negative binomial regression model to calculate the correlation between meteorological factors and E. coli concentrations. From what I know, many environmental variables are strongly correlated, for instance, precipitation and temperature have strong correlation depends on the regional climate conditions. Thus, we should consider the collinearity of environmental variables themselves prior to any multivariate statistical tests were calculated.

 4. This study used more than one data types in binomial regression model. I think ‘the presence of Salmonella’ is a logical variable rather than numeric variables such as precipitation or salinity (Table 7 in section 3.6). I am wondering how to mediate different data types in binomial regression model.

 5. Despite I am not a native English-speaker myself, I see that the language clarity is not at a publishable standard and a language assistance service will definitely help in removing awkward terminologies and sentences.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

The paper addressed  the association between meteorological factors and microbial diversity in coastal oyster-raising area. The bacterial contamination in aquaculture poses an potential health risk, and the paper is in this important field related seafood safety. In general, the paper can be accepted after few revisions.

1) Meterological factors may affect the transport and reproduction in the environment. But the pollution source (e.g. sewage) also plays an important role for the distribution of bacterial contamination. There is lack of the background information about the possible pollution sources in the study. Correspondingly, the discussion on influence from pollution sources should be improved in the discussion section.

2) The unit of sanlinity is not ppt. It has no unit. 

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

The authors present counts of total coliforms, fecal coliforms, E. coli, V. parahaemolyticus and V. cholera and Salmonella spp. in saline waters at six primary locations around the coast of Thailand.  A total of 363 samples were collected between February 2021 and January 2022. There were 30 sampling sites at 5 of the primary locations. It appears that, with the exception of one primary location, each site was sampled once during the wet season and once during the dry season. The authors do not tell us the dates of collection – all on the same date, or spread over a period? However, this needs clarification by the authors. Atmospheric environmental variables were measured at the sampling times, apparently from a nearby Met. station, though the authors are not specific about this, nor do they give locations. They need to clarify this. Standard sample water variables other than microbial were measured.

Table 1 presents Met. Data, but it is not clear over what period the averages are taken. Are the values means at the time of sampling, or over the whole of 2021-22. Since the sampling sites are mainly a few km from land, the relevance of detailed Met. data may be questioned.

Table 4 is useful in showing the prevalence of microbial contamination. Does this differ in different seasonal climates? The standard deviations in table 5 are very large, suggesting domination of the counts by a few very high values. Are high values of the different microbes associated with each other?

The authors carry out a negative binomial regression analysis with primary location and season as factors and E. coli count as the response variable. This suggests rainy season samples are more contaminated. It’s not clear why Fig. 2 has been included. Results of a further regression of E. coli concentrations on a mixture of other microbial data and environmental variables are shown in Table 5. It is not clear why salmonella and fecal coliforms have been included as explanatory variables, since they are natural response variables and not suitable for use in any predictive sense. The extent of correlation between the environmental variables would be interesting to know, and the extent to which the analysis was influenced by extreme values (as suggested by the high SD’d of the counts at each primary location).  Figure 3 is unsatisfactory. It should show data points and some explanation of how the lines have been fitted.

The authors seem to have a good data set which will be of great interest to shellfishery regulatory bodies. However, in terms of science, the statistical analysis and interpretation are inadequate. I have highlighted some issues that need clarification. There is also a need for more and better plots of the raw data, showing the nature of their variability and relationship with each other. I should like these issues addressed.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Dear Editor:

Compared to the original version, this revised manuscript has been carefully addressed all concerns and suggestions. The results and conclusions are solid and convincing.  I believe the revised manuscript fits well to warrant publication in Water.

Author Response

Thank you very much. 

Reviewer 3 Report

The authors have not addressed the following:

1.       Figure 3 should be excluded.

2.       Regression analysis should not include the response variables fecal coliforms and salmonella.

3.       Figure 4 should include data points.

Author Response

Manuscript ID: water-1980029

Meteorological and water quality factors associated with microbial diversity in coastal water from intensified oyster production areas of Thailand

 Author Response File: Author Response.pdf