Microbial Source-Tracking Reveals Origins of Fecal Contamination in a Recovering Watershed

Round 1

Reviewer 1 Report

Limitation of the study (small sample size) should be acknowledge.

Author Response

See attached comments.

Author Response File: Author Response.docx

Reviewer 2 Report

Very well conceived analysis and manuscript for the most part.

One criticism that I feel should be addressed in the paper is the potential for wet-weather events to be a major contributor to fecal contamination. Input from rural and urban sources will of course be very different during wet and dry conditions, and therefore may change interpretation of the importance of rural and urban sources. An acknowledgement of this possibility and suggestion for future work to investigate wet vs dry conditions would suffice.

Although statistical analyses are well done, some investment of additional, graphical representation of results would be valuable, and would improve the accessibility of the paper and the results. [Also, the legend markers in the one plot of spatial patterns should be changed to remove the in-line component - it makes it look like there are different markers in the legend and in the plot.]  

Author Response

See attached comments.

Author Response File: Author Response.docx

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

This paper describes the microbiological fecal contamination in waters collected from a stream catchment, differently impacted by rural and urban settings. The cultivation-based method, applied within the local regulation for water monitoring, was complemented with a qPCR assay with 4 primers targeting bacterial indicator genes (see table 1), in order to discriminate and track the origin of fecal contamination. Some major water physical-chemical (please, do not use “physicochemical”) parameters were also provided and tentatively linked to microbiological contamination levels through a correlative approach.

The manuscript is well-written and structured, but it is not clear how the study outcomes could contribute to the existing knowledge in the field. The study is not clearly driven by a (novel) research hypothesis (see L56-64), and Authors’ intentions are difficult to follow at times.

- There are hundreds of publications combining cultivation dependent and independent methods for water microbiological monitoring and the microbial source tracking by qPCR is well-established since years.

- Moreover, the site description is limited to 10 sampling points and 3 summer days and the dataset provided is likely not sufficiently consistent to “incorporate and validate MST methods into routine monitoring” (see L209-211).

- The statistical analysis is not described in the methods and only preliminary assessed by t-test and correlations. Thus, the mechanisms driving the fecal contamination patterns remain largely unexplored.

- Finally, the overall message is rather trivial, as stated at L213-214 “urban reaches were dominated by human markers and rural reaches were dominated by ruminant markers”, and followed by a number of unsupported speculations on MST modeling, cost-effectiveness, and contamination fate (e.g., L228-230, L251-255, L264-265, L267-269).  

At this early stage, I suggest to rework the study aims and hypothesis to emphasize how your results can contribute in filling knowledge gaps. A solid statistical approach could also help to further understand relations and patterns of fecal contamination in the target site.

Reviewer 2 Report

Manuscript by Green et al. is well written and contain valuable information regarding the application of MST for water quality management. In view of this manuscript can be accepted for publication. I, however, have some concerns that authors might like to address before sending it for publication.

Line 95-96: this line should come first then line 93-95.

Line 103: please add text or reference for FIB enumeration. You have mentioned in line 109 at the moment.

Line 107: add manufacturer.

Quality of both figures (2-3) needs improvement. Marker lined in figure 3 makes difficult to see those markers. Please increase the size of figure 3 and add all sites.

Table 2: Confusing site names, Latitude information is not necessary. Instead, the date of sampling would be good to see. Define class B and C?

Line 175: seven out of 11? Isn’t it 12 (4*3).

Figure 4: could you please define C12?