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Article
Peer-Review Record

Detection of Multidecadal Changes in Vegetation Dynamics and Association with Intra-Annual Climate Variability in the Columbia River Basin

by Andrew B. Whetten 1,* and Hannah J. Demler 2
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Submission received: 12 September 2021 / Revised: 2 January 2022 / Accepted: 20 January 2022 / Published: 25 January 2022

Round 1

Reviewer 1 Report

Reviewer’s Report on the manuscript entitled:

Detection of Multidecadal Changes in Vegetation Dynamics and Association with Intra-annual Climate Variability in the Columbia River Basin

The authors investigate multi-decadal variation of leaf area index (LAI) in the Columbia Watershed, as detected by NOAA AVHRR along with its inter- and intra-annual correlation with maximum temperature and precipitation using the ERA-Interim Reanalysis from 1996 to 2017. The topic is interesting but the manuscript should be better organized and better written. I have several comments to improve the presentation of the paper listed below.

Abstract:

Line 1. It should be “The Leaf Area Index (LAI) is a widely used metric…”

Line 6. Just use the abbreviation LAI here.

Lines 11 and 12. Please rewrite the sentence.

Introduction:

Line 18. Introduction is section 1 not 0.

Lines 93-102. These details should go to the next section describing the study region. In Line 123, you should open a subsection, namely, Section 2.1 Study region. You should also display a map of the watershed here.

Line 116. It should be “inter-annual”.

Lines 117 and 118. I think this is likely due to the delay response. It is likely that the annual and semi-annual components of the climate time series lead the ones in LAI time series (likely there are a few weeks time lag).

The Introduction needs further improvement. Since the authors are investigating the relationship between climate change and LAI, they also need to point out the wavelet decomposition techniques that show the inter-annual and intra-annual variations in the time-frequency domain. For example, the least-squares cross-wavelet analysis (LSCWA) is a new method of coherency analysis and phase differences between the components of two time series. LSCWA, like the Cross-Wavelet Transform (XWT), decomposes the time series into time-frequency domain to obtain a cross-spectrogram which shows how much the components within each time-frequency neighborhoud are coherent and provides the time lag information between the components. However, LSCWA does not require the time series to be equally sampled and can directly analyze time series with missing values and gaps without any interpolation. I suggest the authors to mention the use of LSCWA and XWT for investigating the relationship between climate, vegetation, and streamflow by referring to the following three articles:

https://0-doi-org.brum.beds.ac.uk/10.1016/j.ejrh.2021.100847

https://0-doi-org.brum.beds.ac.uk/10.1016/j.catena.2020.104474

https://0-doi-org.brum.beds.ac.uk/10.3390/rs11222703

Furthermore, these techniques could also be discussed in the discussion part or as the future work.

Lines 119-121. These lines belong to the conclusion section. Instead, please clearly mention the objectives of the paper and mention how the rest of the paper is organized.

Line 148. Please remove the square brackets.

Line 176. Define MSE, Lambda, df, and M.

Figure 1 must be regenerated. There should not be any gray background and also the x-axis and y-axis labels should be enlarged, and the figure should have a resolution of at least 300 dpi. This comment also applies to Figures 5-10.

Line 244. General comment. All the equations in the text must be referred to as Equation (x) not Equation x. Please insert parentheses. The latex command is \eqref not \ref.

Line 262. When starting a sentence with Figure please give the full name. In here, you should say Figure 2. This applies to Line 284, etc.

Figure 3. Please describe what each cluster in the legend represents or give value range.

Line 342. It should be “Figures 6 and 7”.

Figure 4. The appearance can be improved by removing the extra space between the panels. In other words, the x-axis and y-axis of all the panels can be merged as the x-axis values are the same and the y-axis values for each row are also the same. This will remove the extra empty space between the panels and will also enlarge the plots.

The bottom five panels of Figure 4. Why is the precipitation increasing? Is it cumulative?

Line 442. The first reference that I suggested above shows the gradual temperature increase with approximately the same rate 0.3 per decade for the Athabasca River Basin that is near the North of the Columbia River Basin. Therefore, please add that reference here as well.

Line 471. Warmer spring temperature results in melting snowpacks near mountainous regions and increase the streamflow. This has also been described in the first reference that I mentioned above.

Conclusion section is very short. Please briefly mention what the objective was and how you addressed it. Please also mention the limitations of the study here.

Line 105. General comment. Each abbreviation must be defined the first time they appear in the text and their style must be consistent. Please also add an acronym table at the end of the manuscript listing all acronyms used.

Thank you for your contribution

Regards,

Author Response

Thank you for your careful and thorough evaluation of our work. We appreciate your insights, and we have made our best efforts to address your comments. We look forward to continuing the reviewing process with you.

Author Response File: Author Response.pdf

Reviewer 2 Report

Please check the attached file.

Comments for author File: Comments.pdf

Author Response

Thank you for your attention to the details of our work. We feel that your feedback has contributed exceptionally to the improved quality of our updated manuscript. 

 

We look forward to continuing the reviewing process with you.

Author Response File: Author Response.pdf

Reviewer 3 Report

This is a nice paper describing the use of functional data analysis, in particular a functional cluster analysis model, for the detection and analysis of annual greening trends of high dimensional phenological processes. The authors leverage the underlying continuous nature of the data to demonstrate the utility of FDA for studying changes in the timing and magnitude of greenness. The authors present the methods and analysis in a thorough and approachable way, and present the concussions clearly. I have only a few specific comments.

 

Specific comments:

Introduction, Line 87-88: I think there’s a typo in (3). Should it say “(3) the timing and magnitude of the max greenness is retained …”?

Results, Line 284: Address/explain why you chose 5 clusters (k=5).

Author Response

We appreciate your support of our research! We have addressed the few minor suggestions you made, and we thank you for the time you took to evaluate our work.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

I would like to thank the authors for addressing my comments. The manuscript looks better now. Please find the following remaining comments:

The references should be formatted consistently according to the MDPI guidelines. This includes the style of authors' names, year, volume, etc.

Please include the latitudes and longitudes for the study map shown in Figure 1.

Figure 6. All the panels share the same x-axis and y-axis! It would be nice to remove the blank spaces between the panels and enlarge the labels.

The x-axis and y-axis labels (font size) should be enlarged for Figures 2, 6,7,8,9,10,11,12.

Please carefully proofread the article

Thank you for your contribution

Regards,

Author Response

Responses are in blue:

I would like to thank the authors for addressing my comments. The manuscript looks better now. Please find the following remaining comments:

We are happy that the reviewer feels our adjustments our satisfactory, and we have responded to their remaining suggestions.

The references should be formatted consistently according to the MDPI guidelines. This includes the style of authors' names, year, volume, etc.

We have made thorough formatting adjustments to our references section.

Please include the latitudes and longitudes for the study map shown in Figure 1.

Completed. See updated Figure 1.

Figure 6. All the panels share the same x-axis and y-axis! It would be nice to remove the blank spaces between the panels and enlarge the labels.

Blank space removed between panels and axis font sizes are adjustment. 

The x-axis and y-axis labels (font size) should be enlarged for Figures 2, 6,7,8,9,10,11,12.

Font sizes adjusted for all listed figures. 

Please carefully proofread the article.

We have made several small modifications throughout the work. They are largely grammatical changes or minor sentence structure adjustments. We have added one sentence to the abstract and a small paragraph at the beginning of the methods section. After reading through our work, we felt strongly that we did not emphasize the computational feasibility of our method for much larger datasets that the LAI CDR subsetted to the Columbia River Basin. No parallel processing or high performance computing was used in this work which would be required for most clustering problems of this magnitude. We believe that this is an important and easily forgotten highlight of this work without this paragraph and mention in the abstract.

Thank you for your contribution.

We appreciate the timely and thoughtful feedback on our work, and we wish the reviewer a happy start to 2022!

Reviewer 2 Report

The authors appropriately updated the manuscript based on the comments.

Author Response

We are happy that our efforts in revising the manuscript are satisfactory to the reviewer.

During a final proofread of our work, we have added one sentence to the abstract and a small paragraph at the beginning of the methods section. After reading through our work, we felt strongly that we did not emphasize the computational feasibility of our method for much larger datasets that the LAI CDR subsetted to the Columbia River Basin. No parallel processing or high performance computing was used in this work which would be required for most clustering problems of this magnitude or larger. We believe that this is an important and easily forgotten highlight of this work without this paragraph and mention in the abstract.

 

We thank this reviewer for their thorough efforts in reviewing our work, and we hope they have a great and safe start to 2022!

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.


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