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Article
Peer-Review Record

Keystone Soil Microbial Modules Associated with Priming Effect under Nitrogen- and Glucose-Addition Treatments

Forests 2023, 14(6), 1207; https://doi.org/10.3390/f14061207
by Min Xu 1,2, Quanxin Zeng 1,2,*, Yuanyuan Liu 1,2, Chengchung Liu 3, Qiufang Zhang 1,2, Kongcan Mei 1,2, Xiaochun Yuan 1,2,4, Xiaoqing Zhang 1,2 and Yuehmin Chen 1,2,5,*
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3:
Forests 2023, 14(6), 1207; https://doi.org/10.3390/f14061207
Submission received: 25 April 2023 / Revised: 1 June 2023 / Accepted: 9 June 2023 / Published: 11 June 2023
(This article belongs to the Special Issue Forest Soil Carbon Cycle in Response to Global Change)

Round 1

Reviewer 1 Report

Comments for Author,

The fresh organic matter they give to the soil plays an important role in the stabilization of the soil organic matter, as it acts as a prep for the naturally occurring organic separation madness. However, the microbiome is one of the main devices of this preparatory effect in soil systems. Therefore, it was aimed to preserve this precursor effect with the glucose dose determined in different periods. Nonetheless, the aim of this study, the addition of fresh organic material on induced changed natural organic sources, which is related with changing soil enzymatic activity, basal respiration and microbial community. Generally the idea is fine and before acceptance this paper, the paper is needed to revise with these below mentioned shortness. 

-- Please add some data abstract and remoce some of sentences. Because there are many similiar sentences. 

-- Please rephrase these sentences or support with information with lateste refs such as crucial role of enzymatic activty, microbial community  (  Among these factors, microbial properties 47 (e.g., biomass, enzyme activity and community composition) are considered as key factors  in regulating soil PE, as microbially mediated processes, such as microbial respiration and  microbial decomposition of SOM, have been found responsible for PE). Because, you strongly discourse on primer effect relation with these linked factor. 

- ıs it neccessary to add these calculation, I think you can only give briefly, otherwiese ıt makes no sense and more complex. 

"2.3. CO2 analysis and PE "

-- I think the statistical analyses reflect obtained results. Even thus, please discuss on more information regarding a new cumulative CO2 emission. 

-- This sentences should be shifted. Because, this is actually conclusion remark or future recommandation  " Both N and C addition dramatically  shifted the bacterial and fungal community structures. Further analyses of bacterial and  fungal ecological networks and their interactions will provide a different level of understanding of the correlations between cumulative PE and community-level microbial properties in the context of climate change.

--line 496- 497. Please rephrase this sentences. 

Conclusion remark is still missed. Please give some information with Primer Effect or how was change with N or C addition. 

Best Regards

 

 

Some of sentences are needed to rephrases. Especially, Please use more understanable word for reader thoroughly paper. 

 

Author Response

We have responded to each of the questions raised by you, and below we have provided point-by-point responses to all your comments. Plese see the attached Word file 

Author Response File: Author Response.docx

Reviewer 2 Report

The article “Keystone soil microbial modules associated with priming effect under nitrogen- and glucose-addition treatments.identified a bacterial module (B_Mod#3) and a fungal module (F_Mod#5) that predominantly contributed to the changes in cumulative PE under different N- and C-addition treatments, respectively. Felicitation for the good work. I recommend revision with some improvements.

My recommendations:

The references and citation numbers are more than 70 citations, I think it is too many citations.

The figures' resolution needs to be more clear.

Thank you.

 

Author Response

The article "Keystone soil microbial modules associated with priming effect under nitrogen- and glucose-addition treatments." identified a bacterial module (B_Mod#3) and a fungal module (F_Mod#5) that predominantly contributed to the changes in cumulative PE under different N- and C-addition treatments, respectively. Felicitation for the good work. I recommend revision with some improvements.

Response: Dear Reviewer, thank you for reviewing our manuscript. We have revised the manuscript following your suggestions. We believe the changes have improved the overall quality of our manuscript.

 

Specific recommendations:

Q1: The references and citation numbers are more than 70 citations, I think it is too many citations.

Response: We agree and have removed some of the literature.

 

Q2: The figures' resolution needs to be more clear. Thank you.

Response: Thank you for your suggestion. We agree that the uploaded images are unclear, and we have fully updated the figures.

Author Response File: Author Response.docx

Reviewer 3 Report

Keystone soil microbial modules associated with priming effect under nitrogen- and glucose-addition treatments.

 

 

Overall, a very well written manuscript. One I really enjoyed reading. N addition had negative effects on priming effect (PE) but C addition, particularly single C addition, had positive effects. This shifted the microbial community to one that was dominated by saprophytic fungi of the phylum Ascomycota. The authors also identified microbial modules that may explain the effects. Overall, single C addition and N addition could be beneficial for r-strategists and saprophytic fungi that may enhance PE.

 

Introduction

A very well written and self-explanatory section.

 

Methods

 

Line 225: Please add the name of the algorithm used to determine microbial modules.

Line 237: Change “residues” to “residuals”

 

Lines 252-255: Am a little inquisitive, how did the authors apply mixed models to the modules? Were the modules transformed by dimensionality reduction or how? Basically, what was the dependent variable and how was it derived. My knowledge about modules is that they are tightly knitted nodes (OTUS) due to high correlations (positives and negative) between the nodes. They are basically comprised of multiple OTUs in this case. I can see from figure 6c-h that the module values were z-scored and those were used for correlations. What exactly did the authors z-score? The sum of relative abundance/raw values of the OTUs within a module?

 

Results

Line 261: MN was not significant according to the statistics presented in Table 1.

 

Line 294-300 This pattern is not obvious in Figure 2 and there seems to be a mix-up in the figure reference. Also, the subfigures seem to be referenced incorrectly. Please ensure that the figure that you refer to in the text is the one you want to discuss. For example, C-related oxidases should be Figure 2b and C-related hydrolases should be figure 2a.

 

Line 313-316: doesn’t make complete sense particularly line 315.

 

Discussion

Well written section

Author Response

We have responded to each of the questions raised by you, and below we have provided point-by-point responses to all your comments.  Please see the attachment

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Author improved paper carefully, now the paper could be accepted for the publication.

 

Best Regards

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