The Phenophases of Mixed-Forest Species Are Regulated by Photo-Hydro-Thermal Conditions: An Approach Using UAV-Derived and In Situ Data

Round 1

Reviewer 1 Report (Previous Reviewer 2)

Comments and Suggestions for Authors

Critical response on a paper entitled “The phenophases of mixed forest species are regulated by photo-hydro-thermal conditions: an approach using UAV-de- rived and in situ data” resubmitted to Forests by Marín Pompa-García and co-authors

 

The revised version of paper has overcome its major discrepancies mentioned in the initial submission. Abbreviations and terms were mostly clarified or expanded. Figures were mostly upgraded. However, looking through the revised manuscript revealed a few minor discrepancies:

 

Line 91. “created by the authors using QGIS” In my previous comment I’ve asked to clarify the details accordingly satellite image taken to the background (satellite, acquisition date, bands used). No need to specify used software.

L151. Reference on a web-source has to be provided in a separate section.

 

Conclusions. In general, applied updates have overcome existing discrepancies and manuscript worth to be published after the minor revisions.

 

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report (New Reviewer)

Comments and Suggestions for Authors

Reviewer comments for the manuscript titled ''The phenophases of mixed forest species are regulated by photo-hydro-thermal conditions: an approach using UAV-derived and in situ data'' (ID: forests-3717789)

Brief summary

The authors mainly discuss in-situ phenology data and unmanned aerial vehicle-derived phenology data in relation to important environmental variables in a mixed forest in Mexico. The topic is interesting with relevant results which contribute to the literature. However, some issues that need to be addressed for the improvement of the quality of the manuscript are as follows.  

General concept comments

The section of 'Introduction' is considered quite satisfactory, but the inclusion of some additional information regarding the  normalized difference vegetation index, an important component of the current manuscript, in relation with phenology, would be an added value.

'Materials and Methods' needs substantial improvement since essential information is missing. Specifically, regarding the various devices and environmental variables measured (weather station), authors should provide name/s of the model/s, accuracy, and operating range, and name, city, and country of the manufacturer/s. Did a calibration process take place to ensure the reliability of the data?

Authors combined 'historical daily records' with 'previous daily records since July 2023' concerning maximum temperature etc. (lines 123-128), if I understand well. How this combination was implemented? Did this combination lead to a better outcome? Clarify in as much detail as possible. In addition, what was the distance between the study area and the weather station? Also, the authors should provide appropriate reference sources for all websites, e.g. https://power.larc.nasa.gov/data-access-viewer/ (line 125).

 Specific comments

1. Lines 113-114. Apple iPhone 11 with a resolution of 1792 x 828 pixels at 326 ppi and a 113 12 MP camera. Provide the name, city and country of manufacturer for 'Apple iPhone 11' and 'MP camera'.
2. Table 1. Are both 'Sd' and 'Se' necessary since 'Se' can be calculated from 'Sd' and vice versa (n provided)? Also 'Se' is not 'standard error' but 'standard error of the mean' (line 121).
3. Lines 156-159. we analyzed the correlations of... using Spearman’s coefficient. Provide at least one reference source.
4. Line 197. the greenness index What is 'greenness index'? Is this the same as 'NDVI'? If yes, please be consistent with terminology.
5. Table 2. Is the title of the table correct, taking into account the table body?

 

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report (New Reviewer)

Comments and Suggestions for Authors

Dear Authors,

I read this paper with great interest. This paper explores the consistency of multi-species phenological phase transitions with NDVI drone data and its impact on environmental variables. The topic is in line with the research scope of the journal Forest and has scientific significance. The author collected data through field observations for 12 consecutive months, with a solid workload and relatively standardized chart production. However, in order to further improve the quality of the paper, some contents in the manuscript need to be improved. My comments and suggestions are as follows:

Lines 12-28: It is recommended to reconstruct the abstract according to "research purpose → method → ​​key results → conclusion".

Line 84: The map of the study area only marks the longitude and latitude, but does not show the border between Mexico and the United States, nor does it mark the city or state where it is located. This vague statement may cause readers to misunderstand the study area, making it difficult for readers to accurately judge whether the study area is located in the United States or Mexico. Therefore, I suggest adding the geographical element of the border line to the map to clarify the national boundary of the study area, and then add a small-scale regional map to mark the geographical coordinates of the city and surrounding areas where the study area is located to enhance the clarity of spatial positioning.

Line 88: Only one year of phenological observation data is difficult to exclude the interference of abnormal climate years, which makes the universality of the conclusion questionable. For example, the abstract mentions "the impact of extreme drought on phenological period", but lacks multi-year data to support trend analysis. I know that it is difficult for the author to observe continuously for so many years, so I suggest adding a "Limitations" subsection in the discussion section to clearly state the insufficiency of short-term data; if possible, supplement the multi-year NDVI data of neighboring stations for comparative analysis, or suggest subsequent long-term monitoring in the conclusion.

Line 141: The NDVI calculation does not specify whether to correct for atmospheric effects or solar altitude angle. It is recommended to add the NDVI standardization method in Section 2.3.

Lines 163-202: The article only points out the difference in the response of coniferous and broad-leaved trees to light and heat conditions, but does not explain the reasons from the perspective of plant physiology, such as whether the evergreen characteristics of coniferous trees are related to anti-transpiration structures, and whether the deciduousness of broad-leaved trees is regulated by ABA hormones. It is recommended to add an analysis of the physiological differences of tree species in the discussion section, cite plant physiology literature to explain the mechanism of photoperiod regulation of bud germination through photosensitive pigments, and the differences in the effect of VPD on stomatal conductance among different tree species.

Line 240: The article does not seem to cite similar studies comparing the accuracy differences between drone NDVI and satellite remote sensing, nor does it discuss the uniqueness of this research method in mixed forest phenology monitoring. It is recommended to add comparisons with other studies in the discussion section to show the advantages of drone application in heterogeneous forest stands.

Line 60: Should "creased evapotranspiration rates" be replaced with "increased evapotranspiration rates"?

Line 451: Should "avail from the corresponding author" be replaced with "available from the corresponding author"

In summary, this study has clear scientific questions and innovative methods, but there is room for improvement in the positioning of the study area, mechanism explanation, method details and literature comparison. It is recommended that the author make some revisions, deepen the analysis of biological mechanisms, improve the description of methods, and strengthen academic dialogue with similar studies. After revision, the rigor and academic influence of the paper can be significantly improved.

Respectfully,

 

Comments on the Quality of English Language

 

 

Author Response

See PDF file attached

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report (New Reviewer)

Comments and Suggestions for Authors

Reviewer comments for the manuscript titled ''The phenophases of mixed forest species are regulated by photo-hydro-thermal conditions: an approach using UAV-derived and in situ data'' (ID: forests-3717789)

The manuscript is a new revised version and mainly discusses phenology data (in-situ and unmanned aerial vehicle-derived) in relation to important environmental variables in a mixed forest in Mexico. The authors have not adequately addressed all my concerns from my previous review. Therefore, there are still issues that need to be addressed for the improvement of the quality of the manuscript. In my current review, I keep my recommendation of Major Revisions until the clarification of the remaining issues.  

1. Line 124. tion; Se = standard error of the mean. Remove '; Se = standard error of the mean'.
2. Lines 131-133. The recorded variables included maximum temperature (TMAX, °C), minimum temperature (TMIN, °C), and precipitation (P, mm). Regarding 'maximum temperature (TMAX, °C), minimum temperature (TMIN, °C), and precipitation (P, mm)', please provide name/s of the model/s, accuracy, operating range, and name, city, and country of the manufacturer/s.
3. Line 244. Selected linear models of NDVI with the highest coefficient of determination (R² = 0.5), Remove 'with the highest coefficient of determination (R² = 0.5)'.

Author Response

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Author Response File: Author Response.pdf

Round 3

Reviewer 2 Report (New Reviewer)

Comments and Suggestions for Authors

The authors have sufficiently addressed all my concerns and I am pleased to recommend the manuscript for publication.

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

Comments and Suggestions for Authors

1.The content of the introduction is weak. We should first systematically sort out the background, the core contributions and shortcomings of the existing research, and focus on clarifying the methodological limitations and remaining problems, so as to naturally lead to the innovation value and research objectives of this research. It is suggested to further improve the contents of the introduction.

2.In this study, smart phones were used to collect phenological monitoring data. Existing studies should be added to demonstrate the scientific rationality of this method, and the technical feasibility and verification mechanism of mobile devices in the identification of key phenological periods should be explained.

3.It is suggested to supplement the key indicators that characterize the driving mechanism of phenology (such as vegetation physiological parameters: daily photosynthetic rate, leaf area index; Tree structural parameters: tree age, tree height) to strengthen the mechanism to resolve or control potential confounding factors.

4.It is suggested to supplement the description of the method in Materials and Methods.

5.It is suggested to unify the chart layout specification and adopt the nearest layout principle of text and graph to enhance the logical coherence of data presentation. It's a good idea to place the appendix in the same place as Results for easier reading.

6.It is suggested to visualize the Spearman correlation coefficient matrix through heat map, supplemented by hierarchical clustering analysis, to systematically reveal the correlation strength and potential relationship structure between variables. Easy to read.

7.Only one year of variability was explored in this study, which is not enough to explain the long-term response of plants to environmental changes. It is recommended to refine the monitoring scale and extend the monitoring time and scope.

Reviewer 2 Report

Comments and Suggestions for Authors

Critical review on a manuscript entitled “The Transition of Multispecies Phenophases Corresponds with NDVI Drone Data Influenced by Environmental Variables”, submitted by Marín Pompa-García and coauthors to Forests

 

The written manuscript considers the application of NDVI product derived from drone observations and in-situ picture taking for investigating of phenological phases of different plant genuses. Authors have also used variable set including photoperiod, deficiency of vapor pressure, maximum temperature and precipitation to study their partial influence over NDVI. Authors provided numerous appendices and a data table (Table 1). Despite all the importance of the selected topic, reading of the labor has revealed some discrepancies and issues that need to be solved to increase paper importance for the international reader.

Line 31. Are climate variations really “exacerbated”? Isn’t that sentence biased? What can prove it? Does it really produce value for the paper?

L50-55. That clarification requires an explanation of what the “overstudied system” is and to what extent studying affects a system under a scope?

L95-102. The UAV payload including spectral characteristics and bandwidth has to be explained in details and cited.

L107. ANOVA is never expanded.

L110. Website has to be cited properly. R scripts authors developed can be shared (Data availability section) to support research reproducibility.

Figure 1. Despite claims in Abstract section (L22-23) seasonal changes look synchronous due to coinciding boundaries. Also, abbreviations for seasons (Au, Wi, Sp, Su) have to be expanded. Not clearly understood: “The correlation values of climate variables are denoted by colored horizontal lines”. With their distances from the bottom? Their relative horizontal length? Or their length are showing observation period? Besides, colors for curves for 4 genuses aren’t explained at all. That plot seems overcomplicated! Better to possible simplify it of decomposed into the different plots.

Section 3.2 and Table 2. Not clearly understood why authors created a set of linear models for each predictor variable separately.

Fig A1. Inset map a) has to explain source of the imagery, acquisition date and used bands. If image is obtained from a mapping service, please, refer.

Figures and tables D1,D2 is never referenced in a text!

Unfortunately, arbitrary design of linear models set separately for every single predictor variable doesn’t let to compare their contribution into the target variable. I’d recommend to use two separate models involving all predictors, for instance multiple polynomial regression model vs random forests, then accuracy metrics will allow to choose the most advantageous. That will make conclusions of the “Discussion” section data-driven, allowing to determine predictors ACTING seasonally. Data-driven research design doesn’t refer on anyone’s experience or opinion like authors do so far.

References onto appendices makes readers constantly scroll text back and forth that decrease convenience. Please, consider reorganization of the paper structure.

 

Conclusions. Based on mentioned above, I recommend major research redesign making it data-driven. It will shorten and substantially ground “Decisions” and “Conclusion” sections making them unbiased.

 

 

Reviewer 3 Report

Comments and Suggestions for Authors

Abstract: Scientific papers should be written using a formal language with impersonal expressions. Please, replace "Here, we evaluate", "we compared" with "in this paper, the correspondence...,has been evaluated" , "it has been compared" etc.

row 63 and 78: replace "We hypothesized" and " we photographed ", respectively

row 201 "our hypothesis. Our study " idem

row 68 and 102: replace "a site was chosen " with "a site has been chosen" , "was then calculated" with "has been calculated", since it is a completed action before the moment of speech.

row 400: "Observations made in situ demonstrated a divergence of phenological patterns between conifers and broadleaves, with the former maintaining their evergreen foliage, 
while the latter shed theirs, which is attributed to an eco-physiological strategy to optimize available resources" - this is nonsense. Coniferous, by definition, maintain their foliage, hence the name evergreen and this is not "attributed to an eco-physiological strategy to optimize available resources".

Reviewer 4 Report

Comments and Suggestions for Authors

The topic is interesting; however, the experimental design and the corresponding results do not convince me. Are the results and conclusions generalizable?

 

Major comments：

1. Abstract: The authors mention "drought" multiple times, specifically in Lines 11 and 25. However, I did not find any indicator representing drought in this study. Additionally, there are four categories of drought (meteorological, hydrological, agricultural, and socioeconomic). Could authors clarify which category or categories have been explored in your research?

 

2. Introduction: The author should reference key studies and clearly state their contributions and limitations. Without this, it is difficult to understand the current state of research and how this study builds upon or differs from existing work.

 

3. “3.2. Environmental and phenology relationships”: How many samples were used to obtain the experimental results? Are the results generalizable?

 

4. “4. Discussion” Line 353: Above all, the high susceptibility to drought episodes. How do you define drought episodes? I cannot find sufficient results to support it in this paper.

 

5. Conclusions: The authors should align the conclusion section with the key questions proposed in the introduction to provide a clear and cohesive summary. Please remove some redundant sentences from the conclusion section that cover well-known information (for example, lines 399–402).

“We addressed the following specific questions: How do the monthly phenophases transition within tree species? Is there a biological correspondence between ground data of phenological events and NDVI values derived from UAVs? How are these driven by climate data? We hypothesized that there is substantial differentiation between species showing a temporal coupling across ground-data phenology and those detected by UAV, which is in turn driven by intra-annual photothermic and hydroclimatic drivers. ”

Lines 399-402: “Observations made in situ demonstrated a divergence of phenological patterns between conifers and broadleaves, with the former maintaining their evergreen foliage, while the latter shed theirs, which is attributed to an eco-physiological strategy to optimize available resources.”

Minor comments：

1. Keywords: Vegetation indices include NDVI. Authors use vegetation indices and NDVI as keywords in the meantime.

 

2. “ Materials and Methods”: The authors should specify the seasonal divisions in this section by clearly indicating which months correspond to spring, autumn, and winter, as this information is currently missing. Authors use the seasons division in Lines 145-157.

 

3. Lines 80-82: It is challenging to achieve completely consistent photographic conditions over the course of a full year. Factors such as seasonal changes in sunlight angle, atmospheric conditions, and weather variability inevitably affect lighting and color balance, even when maintaining the same azimuthal orientation, exposure settings, and time of day for each shot.

 

4. Lines 85-90: The authors only specified the temporal resolution of the datasets, but did not provide any information about their spatial resolution.

 

5. Lines 87-90: Please add the reference for the features used in this study (such as maximum temperatures (TMAX, °C), minimum temperatures (TMIN, °C), precipitation (P, mm), and photoperiod.

 

6. Figure 1：Please correct the error “Spearman [0.4 ≤ r ≥4]”. Additionally, please provide the full names for all abbreviations used in Figure 1, including Au, Wi, SP, etc., as well as for n, d, j, F, and other similar notations. The use of unexplained abbreviations upon first mention may cause confusion for readers.

 

7. Figure A1. d) Please clarify the meaning of the abbreviation on the x-axis by providing its full form. Does the precipitation drop to zero in some months?

 

8. Table 2. Please keep the same decimal place in Table 2.