Forest Landscape Model Initialization with Remotely Sensed-Based Open-Source Databases in the Absence of Inventory Data

Round 1

Reviewer 1 Report (Previous Reviewer 2)

The paper is interesting, but it needs to be improved further.

Introduction

Please consider adding more references at international level.

2.2.1. Sites and ecoregions-Please provide a more detailed description of sites and ecorregions.

2.2.1. Sites and ecoregions-Why the time limit of 200 years?

Figure 2. Soil polygons.-Map lacks a scale legend and orientation.

4. Discussion

Many studies-Others may be mentioned.

427-430-Detail better these ideas.

5. Conclusions-Well done.

 

Author Response

Dear reviewer!

Thank you very much for your careful review of our manuscript and for the valuable and important comments that helped us to improve our work!

The paper is interesting, but it needs to be improved further.

Point 1. Introduction. Please consider adding more references at international level.

Thank you for that suggestion. We have added more international level references in the Introduction (Line 44 [7-9], Line 62 [16, 17], Line 83 [21])

Point 2. 2.2.1. Sites and ecoregions-Please provide a more detailed description of sites and ecorregions.

We have expanded the description of the sites and ecoregions.

“The smallest area unit in LANDIS-II is a site, homogeneous in terms of its parameters (light level, soil, etc.). Different tree species of different ages may be present on a site at one point in time. Sites can be combined due to the limitations of initial data and computer resources required to perform model calculations…

In LANDIS-II, the study area is divided into different land types or ecoregions. An ecoregion is one or more cells united by similar ecological conditions (climate, soil, etc.) that influence succession and disturbance processes. The selection of such objects makes it possible to use their parameters to rank the influence of environmental conditions on the forest in different parts of the study area. For example, the model can set the probability of establishment or death of a species in each ecoregion.”

Point 3. 2.2.1. Sites and ecoregions-Why the time limit of 200 years?

This is an interesting and important question, and we have added an explanation in subsection 2.4 Model simulation and provide it here:

“The duration of the simulation period was set at 200 years. This duration is due to the specificity of the study area: there are many coniferous trees with an average life cycle of 200 years. Therefore, over the selected period we can trace the cycle of natural dying and subsequent regeneration of the forest in the study area.”

Point 4. Figure 2. Soil polygons.-Map lacks a scale legend and orientation.

Thank you for this comment, we have modified Figure 2 and added a scale bar and orientation to it.

4. Discussion

Point 5. Many studies-Others may be mentioned.

We have added more references to the other studies: Line 418 [14, 36-39]

Point 6. 427-430-Detail better these ideas.

We have expanded the description in the above paragraph.

“With the development of machine learning methods and improvement of remote sensing data quality, it became possible to classify areas occupied by specific tree species on satellite images With the development of machine learning methods and improvement in the quality of remote sensing data, it became possible to identify individual tree species in images [40–44]. Here, it is possible to separate different species with 95-97% accuracy in high and ultra-high resolution images, which makes it possible to build detailed maps of forest species composition based on classification materials. If a training sample is available, this approach makes it possible to conduct an automated forest inventory.”

Author Response File: Author Response.pdf

Reviewer 2 Report (Previous Reviewer 3)

A major revision was provided.

I suggest that the manuscript can now be accepted for publication.

Author Response

Dear reviewer!
Thank you very much for your work with our manuscript!

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

the study seems very much interesting. However, the present form is not suitable for publication in Forests.

1. The introduction is not sufficient.  For example, the phrases in lines 78-83 are too hasty. More details are needed to justify you research!

2. the advantages of your study, especially the advantages of your methodology, is missing!

3. All of the Latin names of the species are not italic type. It is a common knowledge in scientific writing!

4. Figure 1 the location of the study site should be in larger scale, and I could not get image of where it is in the world!

5. Why the study area is suitable for your study? Give reasons

6. you say the models have advantages, How to fulfill it? however, I have not find the source codes to run the models.

7. the WorldClim datasets in the near current conditions (1970-2000) are too old. Maybe, you should retrieve the updated dataset from CRU.

8. in such small scale, why not field validation?

9. the open sources you mentioned are just some new predictors from online datasets? In my opinion, open data is the mega-data and can be real-time updated.

10. the discussion is too hasty and cannot convince me. You did not testify the advantages of your study or you methodology.

Author Response

the study seems very much interesting. However, the present form is not suitable for publication in Forests.

Thank you very much for the review and tips to improve our work! We significantly revised the manuscript, supplemented the description of the methodology, added additional tables to improve understanding the material.

1. The introduction is not sufficient.  For example, the phrases in lines 78-83 are too hasty. More details are needed to justify you research!

- We changed the “Introduction”, added more details about model, used dataset, etc.

2. the advantages of your study, especially the advantages of your methodology, is missing!

- The advantage of our work is to combine data from different sources to get the initial data for FLM, because it is not possible to map the initial conditions for the model if detailed field data are not available. We have added a more detailed description of our methodology in the subsection 2.3.2.

3. Allof the Latin names of the species are not italic type. It is a common knowledge in scientific writing!

-Sorry for such a gross mistake, we didn't notice that the italic was missing when formatting the article in the publisher's format.

4. Figure 1 the location of the study site should be in larger scale, and I could not get image of where it is in the world!

- The study area image was changed, we added more general map and legend.

5. Why the study area is suitable for your study? Give reasons

- We live near Lake Baikal, so we traditionally study everything related to it, including forests near the coast. The study area has 95% lands covered with forest and is located near Baikal, therefore, it seemed to us very suitable for studying.

6. you say the models have advantages, How to fulfill it? however, I have not find the source codes to run the models.

- The LANDIS-II model really has many advantages (various extensions of succession and disturbances, flexible interaction settings, etc.) and therefore is the de facto standard in the field of forest modeling. All source codes are on the official website: https://www.landis-ii.org

7. the WorldClim datasets in the near current conditions (1970-2000) are too old. Maybe, you should retrieve the updated dataset from CRU.

- Yes, you are right, the WorldClim data is not the latest. In this study, we only needed to understand the general trends in differences in climate data across study area, so it is acceptable to use the WorldClim data. Unfortunately, we were unfamiliar with the CRU dataset, but we plan to use it in the future. Thank you very much for the suggestion!

8. in such small scale, why not field validation?

- We think the study area not small: 213000 ha of the forest lands. In this work, we used 200 randomly selected points, the land cover of which was established using high resolution images to assess the accuracy of the classification products. Unfortunately, the available inventory data for our study area is significantly outdated, the date of their collection is 10-15 years ago.

9. the open sources you mentioned are just some new predictors from online datasets? In my opinion, open data is the mega-data and can be real-time updated.

- We relied on the definition that open data is free and freely available. The main idea of the open data - anyone can access, use and share it.

10. the discussion is too hasty and cannot convince me. You did not testify the advantages of your study or you methodology.

- We added a more detailed description of our methodology in the subsection 2.3.2, five supplementary tables in Appendix A, and expanded the “Discussion” to better explain the advantages of our method.

Reviewer 2 Report

The paper is interesting, but it needs to be improved further.

Main remarks:

Introduction

L49-52-Other references may be included.

The objective and contribution is well described.

2.3.1. Tree species

L149-150-But this still limited.

L179-180-Specify quantitatively the validation carried out.

The rest of data treatment procedures are well described.

Discussion

L327-328- "Biomass Succession does not include possible human impacts on the forest and dis turbances, considering only natural succession." It would be interesint to discuss the introduction of possible human inpacts in the model in the future.

Author Response

The paper is interesting, but it needs to be improved further.

- Thank you very much for the review and tips to improve our work! We significantly revised the manuscript, supplemented the description of the methodology, added additional tables to improve understanding the material.

Main remarks:

Introduction

L49-52-Other references may be included.

-Thanks for the advice, we added more references about the model

The objective and contribution is well described.

2.3.1. Tree species

L149-150-But this still limited.

- You are absolutely right, the use of our approach is based on a number of simplifications, which can certainly reduce the quality of the simulation results. However, in the absence of inventory data and the impossibility of mapping the initial conditions for the model, we believe our approach is justified. We have added a more detailed description of the problem of the limitations of our approach in the “Discussions”.

L179-180-Specify quantitatively the validation carried out.

- We have not validated the AGB data discussed in this subsection 2.2.4. This is the data by GlobBiomass project, you can find out about the features of their processing on the: https://globbiomass.org/

The rest of data treatment procedures are well described.

Discussion

L327-328- "Biomass Succession does not include possible human impacts on the forest and dis turbances, considering only natural succession." It would be interesint to discuss the introduction of possible human inpacts in the model in the future.

- You are absolutely right, it is very interesting to add the parameters of logging, fires, forest diseases, and other disturbances to the model. Unfortunately, nowadays in the real world, the forest rarely has only natural dynamics. The purpose of this work was to show the collection of initial data for the basic configuration of the model, but later we will definitely move on to taking into account various impacts on the forest.

Reviewer 3 Report

Dear Editor Forests

Dear Authors

This is the reviewer report for:

 Manuscript ID: forests-2469552

Type of manuscript: Article

Title: Forest Landscape Models Initialization with Satellite Data in the Absence of Inventory Data

Authors: Igor Bychkov, Anastasia Popova *

Submitted to section: Forest Inventory, Modeling and Remote Sensing,

 Summary

The manuscript tackles the important issue of using remote sensing derived data in the absence of inventory data to initialize the forest landscape model Landis-II. To that end, several open-source databases remotely sensed-based regarding climate, elevation, soils, land cover, and aboveground biomass were used. The Landis-II model was initialized, using as study area the Goloustnenskye forestry area (Russia), by setting its ecoregions, tree species and trees age, to perform a 200-years biomass succession simulation. The data to set the ecoregions (precipitation, maximum temperature, minimum temperature, elevation, and soil) was derived from the WorldClim database (monthly averages 1970-2000), SRTM data, and the Soil map of Russia. Tree species maps were obtained from both the FROM-GLC (2015) and GLC_FCS30-2020 databases and after compared using a sample of 200 forest inventory points to set its accuracy. Trees age by species map was derived from the ESA Biomass Climate Change Initiative (2018). Firstly, the biomass data were compared to the study area forest inventory data (2018) by species and age classes. Secondly, biomass and age classes were compared to study area growth and productivity data to obtain a correspondence/correlation and generate a map for species and age composition. After, obtaining the initialization parameters the simulation was performed using biomass and climate data.

I hope my suggestions/comments will be useful to improve the manuscript. Congratulations for the interesting article that I had the opportunity to revise.

 

General comments

 The theme investigated in this manuscript is very interesting. However, the manuscript needs a major revision to clarify the problem being investigated, the methodological approach used, the results obtained and its impact. English editions are also needed. The “Introduction” section needs to be improved regarding the Landis-II model and the open-source databases available, particularly the ones with valuable data to respond to the lack of inventory data or field data. The “Material and Methods” section should focus on “what was done” only thus general considerations are advised to be moved to the “Introduction” section. Likewise, the “Results” section should focus on “what was obtained” only thus paragraphs regarding methodological procedures must be moved to the “Material and Methods” section. The “Discussion” section needs some improvement particularly regarding validation/limitations by using remote sensing/alternative data to overcome the lack of inventory data or field data. The “Conclusion” section needs improvement to be aligned with the previous section by focusing on this study investigation problem: the use of remote sensing/alternative data in absence of inventory data. Finally, the Abstract needs to be rewritten to express the improvements suggested.

 Specific comments

 Title

Since, the authors did not explicitly use remote sensing data in this study but only Open-source Databases Remotely Sensed-based it is suggested to adequate the title as follows:

Forest Landscape Models Initialization with Open-source Databases Remotely Sensed-based in the Absence of Inventory Data

Abstract

It should be improved in the view of the comments made to respond to the following issues: Context or Background/Aims/Methods/Results/Conclusion.

Introduction

It should be improved to respond to the following issues: “what it is known?”; “what it is not known?”; “how is going to be made?”.

Introduction is quite short thus it can accommodate some general paragraphs from “Material and Methods” section regarding the Landis-II model (lines 99-112) and the open-source databases available (see Table 1 – broadly summarize in a paragraph), particularly the ones with valuable data to respond to the lack of inventory data or field data (lines 156-170), the core of this investigation.

Line 51 – “biomass volume” please change to “biomass”. Biomass refers to a weight (Mg/ha or g/m²) not a volume (m³).

 Material and Methods

The “Material and Methods” section should present “what was done”: 2.1 Study area; 2.2 Data; 2.3 Procedures – Landis II; 2.3.1 Model initialization (input parameters); 2.3.2. Model simulation (output parameters/maps). 

 2.1 Study area

Figure 1 – captions should identify first (a) the general map at the right and legends must be added (Russia, Irkutsk) to give geographic context of the study area location; second (b) the map at the left, the Goloustnenskye forestry area – the study area itself.

 2.2 Data

Please, identify the databases used in this study (date and special resolution) and the parameters to be extracted for the Landis-II model (see Table 1 – keep the databases used in this study only and add the parameters to be extracted). For instance, it is not clear from which database “Elevation” (and its spatial resolution) was extracted from (see Table 1 – no information).

Please, explain the assumption of using aboveground biomass to infer tree age.

Line 198 – “biomass volumes” please change to “biomass”. Biomass refers to a weight (Mg/ha or g/m²) not a volume (m³).

2.3 Methodological approach – Landis II model

The “Material and Methods” sub-sections presentation should follow the same sequence of “Results” section (the ecoregions map; the minimum temperature, maximum temperature, precipitation, and elevation maps; the land cover classification maps essayed; the species and age composition map; and the aboveground simulations map).

 Line 248 – “a height map” please change to “an elevation map”.

 2.3.1 Model initialization (input parameters)

Please, explain step by step how the initial parameters were extracted (see Table 1 – databases; parameters are missing), and the assumptions/decisions made regarding species class used in this study. For instance, ecoregions (e.g., lines 239-251; 268-279).

Tree species (e.g., lines 273-279; 300-305; 312-324). For instance, highlight that tree species were compared both from the FROM-GLC (2015) and GLC_FCS30-2020 databases. Explain how the accuracy of these databases were evaluated for the study area as there are results presented in Figure 4 and Table 3.

Trees age (e.g., lines 300-305; 312-324). Trees age was derived from the ESA Biomass Climate Change Initiative (2018). However, it is not clear how the relationship between aboveground biomass and age was obtained. Indeed, there is a logistic relationship between growth (e.g., volume, biomass, carbon sequestration…) and age. However, the shape of the curve depends not only on age, but also on the site productivity and stand/forest density/stocking. Therefore, assumptions made in this study and how they were made should be better explained. Please, information how the relationship between aboveground biomass and age was supported by the references: Forest Plan – inventory data 2018 [27] and Tables and Models of Growth and Productivity of Forests of Major Forest Forming Species of Northern Eurasia [25]. Provide supplementary information/data in Appendix if necessary.

This step of assessing trees age is crucial to the body of this study investigation: the use of remote sensing data in absence of inventory data. Indeed, the ESA Biomass Climate Change Initiative (2018) was produced by using remote sensing data even though the authors did not explicitly use remote sensing data in this study.

2.3.2. Model simulation (output parameters/maps). 

Please, move the explanations/assumptions/considerations that are in “Results” section regarding model simulation (e.g., lines 327-345).

Average evapotranspiration is needed but there is no data about this parameter in any Table.

Likewise, the ANPP and AGB parameters calculation according to the Tables and Models of Growth and Productivity of Forests of Major Forest Forming Species of Northern Eurasia [25] should be clarified. For instance, provide a summary table with the models used for each parameter estimation by species in the “Material and Methods” section or in the Appendix.

 Please, explain how Establish probability and Mortality probability were set.

 Line 240 – “biomass volume” please change to “biomass”. Biomass refers to a weight (Mg/ha or g/m²) not a volume (m³).

Results

The “Results” section must be focused on the results obtained in Figures 2 to 7 and Tables 2 to 4. All paragraphs regarding of how it was made, and the assumptions/decisions taken must be moved to the “Material and Methods” section.

This section follows the sequence of presenting first the ecoregions map; after, the minimum temperature, maximum temperature, precipitation, and elevation maps; then, the land cover classification maps essayed; the species and age composition map; and at the end, the aboveground simulations map. Thus, the “Material and Methods” sub-sections presentation should also follow this sequence to improve clarity on the methodological approach used in this study.

Please, provide the correspondence tables between aboveground biomass and age supported by the references: Forest Plan – inventory data 2018 [25] and Tables and Models of Growth and Productivity of Forests of Major Forest Forming Species of Northern Eurasia [27]. Provide supplementary information/data in Appendix if necessary.

In table 4 please explain the values set in columns: Establish probability and Mortality probability.

Please, change “Perceptation” to “Precipitation” in Figure 3c.

Line 322 – “biomass volume” please change to “biomass”. Biomass refers to a weight (Mg/ha or g/m²) not a volume (m³).

Figure 5 – it is not clear the species and age combination. A color shade scale would be helpful.

 

Line 344 – “biomass volume” please change to “biomass”. Biomass refers to a weight (Mg/ha or g/m²) not a volume (m³).

Figure 6 – vertical axis please change units to g m^-2

If the notation g m^-2 is to be adopted, then it must be used throughout the manuscript for consistency purposes (e.g., Table 4).

 Discussion

The “Discussion” section is quite short and needs some improvement particularly regarding validation/limitations by using remote sensing/alternative data to overcome the lack of inventory data or field data.

 Conclusions

The “Conclusion” section needs improvement to be aligned with the previous section by focusing on this study investigation problem: the use of remote sensing/alternative data in absence of inventory data.

References

There are some incomplete references (e.g., lines 444, 456, 477, 480).

Comments for author File: Comments.pdf

none

Author Response

Dear reviewer,

My co-author and I thank you for the time devoted to our paper, constructive detailed proposals, and attention to detail. We are very pleased that you have done such a great job of studying our manuscript, delving into the smallest details, and have shown us directions for improvement.

We carefully studied all comments and tried to revise our manuscript point by point. Changed parts of the document are highlighted by the " Revision " function. My answer is below in file.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Just as my previous comments, the manuscript has not reach a standard fro publication in Forests because its has fundmental flaws.

Reviewer 3 Report

Dear authors

Dear Editor

All the proposed changes and/or improvements were made.

Best regards