Allometric Models to Estimate the Biomass of Tree Seedlings from Dry Evergreen Forest in Thailand

Round 1

Reviewer 1 Report

In this manuscript, the authors developed an allometric equation to predict seeding biomass from the morphological traits (root collar diameter, shoot height, main stem length and wood density of seedlings). actually, obtaining allometric equation for allow measurement of seedling biomass without disturbing the seedlings. From a point of view of the proposed seeding biomass method, I recognized the interest of this work. Thanks to the best-fit and alternative models of the seedling biomass provided by slight difference, it was showed that the wood density can be omitted in a larger scale study without the resource to measure seedlings wood density. Nevertheless, in the present version, I think that the wider applicability of these allometric models should be proved.

 

Over the past few decades, we have many other methods to fit the biomass models and some of these methods were widely recognized because they worked well. Hence, it was necessary to showed the advantages of the statistical method when compared to the present commonly used methods (such as additive biomass equation). On the other hand, the authors point out that the plants' ability to fix and store carbon differs depending on the environment and the species of the plant. Why don't the authors test some more environment variable and provide detailed information on biomass differences among species or groups (understory, sub-canopy and top canopy), such as different restoration environments. On the other hand, I noticed that the SL (shoot length) and SH (shoot height) are both variables representing plant height, but the contribution of the two variables is quite different when fitting the model (Table 2). Is this mainly caused by the seedling morphological traits or the difference of species or groups? Besides, the use of species as a random effect was reasonable in study (in lines 246-247), and the random effects used here seem to be easily misunderstood as random effects used in building mixed effects models. A larger data may be necessary to test the random effects of the allometric method.

Overall, I recommend a revision of more testing for the allometric model.

 

Detailed comments follow:

 

Lines 263-264: The d b and c are not consistent with the figure content.

 

 

 

Author Response

Response to Reviewer 1:

In this manuscript, the authors developed an allometric equation to predict seeding biomass from the morphological traits (root collar diameter, shoot height, main stem length and wood density of seedlings). actually, obtaining allometric equation for allow measurement of seedling biomass without disturbing the seedlings. From a point of view of the proposed seeding biomass method, I recognized the interest of this work. Thanks to the best-fit and alternative models of the seedling biomass provided by slight difference, it was showed that the wood density can be omitted in a larger scale study without the resource to measure seedlings wood density. Nevertheless, in the present version, I think that the wider applicability of these allometric models should be proved. 

• Thank you for your on-point summary of our manuscript. We appreciate your feedbacks and will try our best to respond to your concern. The edited text will appear in red in the revised manuscript.

Over the past few decades, we have many other methods to fit the biomass models and some of these methods were widely recognized because they worked well. Hence, it was necessary to show the advantages of the statistical method when compared to the present commonly used methods (such as additive biomass equation).

• We recognize that other methods are also available for biomass estimation. Our current statistical method had an advantage in its simplicity and ease for applying with the seedling measurement. The additive biomass equation has a particular advantage in enhancing consistency when adding up multiple components of biomass, such as stem, bark, and leaf. In the case of seedlings, we did not experience problems with additivity, probably because the leaf and bark components were relatively minor compared to the stem. Therefore, we chose the traditional allometric approach for our seedling data. We have added this discussion into our manuscript.

On the other hand, the authors point out that the plants' ability to fix and store carbon differs depending on the environment and the species of the plant. Why don't the authors test some more environment variable and provide detailed information on biomass differences among species or groups (understory, sub-canopy and top canopy), such as different restoration environments.

• In our exploratory analysis, we found no significant biomass differences among the plants from different canopy layers at the adult stage. These seedlings were also grown in the common environment. Therefore, it is less likely that they were affected by different growing conditions in this case. We have added this explanation in the method section.

On the other hand, I noticed that the SL (shoot length) and SH (shoot height) are both variables representing plant height, but the contribution of the two variables is quite different when fitting the model (Table 2). Is this mainly caused by the seedling morphological traits or the difference of species or groups?

• SL and SH both represent plant height in a broad sense. However, in many seedlings, the stem does not stay upright, resulting in drooping, curved shoot. In these cases, SL is larger than SH, which explains why these two variables have different contributions. We have added this explanation into the method section.

Besides, the use of species as a random effect was reasonable in study (in lines 246-247), and the random effects used here seem to be easily misunderstood as random effects used in building mixed effects models. A larger data may be necessary to test the random effects of the allometric method.

Overall, I recommend a revision of more testing for the allometric model.

• We agree that a larger data may be necessary to test the random effects. Unfortunately, due to the limited available seedlings, we could not perform more testing for the model at this point.

Detailed comments follow:

Lines 263-264: The d b and c are not consistent with the figure content.

• Our apology for this mistake. The caption has been corrected.

Reviewer 2 Report

Dear authors

The manuscript is written good and intersting but having so many loopholes which may be rectified by you as I mentioned.

Comments for author File: Comments.pdf

Author Response

Response to Reviewer 2:

The manuscript entitled Allometric Models to Estimate the Biomass of Tree Seedlings from Dry Evergreen Forest in Thailand written very well but having some issue below as given:

• We appreciate your feedbacks and will try our best to respond to your concern. The edited text will appear in red in the revised manuscript.

1. In abstract line no 20, why authors use only 205 seedlings, is it any specific model or why you use specifically?

• We grew more than 1,000 seedlings but only a fraction of them survived at two years. We selected the species of seedlings with enough replications, which resulted in the 205 seedlings reported here.

2. In abstract, line no 23, pls explain what did you mean there?

• Our study here measured the seedling biomass and traits in the pot-grown conditions, which may result in different biomass than what we might observe in the actual forest. We explain this part further in our discussion (L.299-305).

3. In abstract, please give output and conclusion in one sentence for the novelty of this research.

• We have added the sentence to highlight the novelty of this research.

4. Keywords should be different from the title.

• Thank you for your suggestion. We have adjusted the keywords accordingly.

5. Line no 68, refrase this sentence.

• We have removed this sentence to improve the flow and clarity of the statement.

6. In methodology, line no 106, correct the years

• We have corrected the year per your suggestion.

7. In table 1, you used no of seedlings differently, why you use different number of seedlings for the study? Why not equal number of seedlings you choose?

• As stated earlier, we grew our seedlings from the seeds collected from the nature, which resulted in typically low germination rates. We included as many seedlings per species as we could to ensure the quality of the model. We understand that unequal sampling among species could affect the comparison among the species. However, our statistical approach treated species as a random effect, instead of fixed effect, to avoid such a problem.

8. How many replications you used for this study?

• The replications for each species are reported in Table 1.

9. I am wonder that authors didnt use any statistical software for statistical analysis.

• We used R, which is a free software environment for statistical computing and graphics, as stated in the lines 173-174.

10.in table 2, line no 182 to 184, what do you mean about this sentence.

• We have modified the text in the caption to explain our table better.

11. Discussion part is different from results part as it is very confusing so clear the result and discussion part to each other.

• We apologize that our sections were different between the results and discussion. We have modified the sections, so that 3.1 and 3.2 in the results now match with 4.1 in the discussion. The rest of discussion expanded on what we learned from the results and took on different headings.

12. Why authors not add any conclusion part for this study?

• We have now added a conclusion section per your suggestion.

13. English language should be improve throughout the paper.

• We have re-checked our English grammars and style throughout the manuscript with a software and an English native speaker.

14. Follow the guideline of the journal.

• We have consulted the journal guideline and tried our best to adhere the instruction from the journal.