Next Article in Journal
Research on the Identification of Particleboard Surface Defects Based on Improved Capsule Network Model
Previous Article in Journal
Preliminary Study: Micropropagation Using Five Types of Chelated Iron and the Subsequent Acclimation of Blue Honeysuckle (Lonicera caerulea var. kamtschatica Sevast.)
 
 
Article
Peer-Review Record

Effects of Climate on Stand-Level Biomass for Larch Plantations in Heilongjiang Province, Northeast China

Forests 2023, 14(4), 820; https://doi.org/10.3390/f14040820
by Surya Bagus Mahardika 1,†, Shidong Xin 1,†, Weifang Wang 1,* and Lichun Jiang 1,2,*
Reviewer 1: Anonymous
Reviewer 2:
Forests 2023, 14(4), 820; https://doi.org/10.3390/f14040820
Submission received: 13 January 2023 / Revised: 27 March 2023 / Accepted: 13 April 2023 / Published: 17 April 2023
(This article belongs to the Section Forest Inventory, Modeling and Remote Sensing)

Round 1

Reviewer 1 Report

Review of Forests 2190509 Effects of climate on stand-level biomass for larch plantations in Heilongjiang Province, Northeast China

General comments:   I have no dispute with the fitting procedure and the method advocated by Parresol for attaining additivity among the biomass components.  The weighting procedure for each component is also appropriate.  I do question however, the premise behind the study, namely that, incorporating climate data is recommended to improve stand biomass modeling and reduce uncertainties related to forest biomass and carbon stocks.   At the very least, a system of three equations is required to model forest biomass including: (a) a dominant height equation; (b) a basal area prediction equation; and (c) stand-level biomass prediction equation.  I see no advantage with models M1 - M4 over the He (2015) approach where stand-level biomass is a function of localized parameters and stand-level volume (m3/ha).

 

Specific comments:

 Line 90:  The following statement appears to be the reason for the study: incorporating climate data into the model was highly recommended to improve further stand biomass modeling and reduce uncertainties related to forest biomass and carbon stocks.  What is the basic hypothesis here?  Are the authors implying that precipitation and temperature are responsible for explaining changes in wood density and dry weight? 

 Line 137:  This is a rather low sample size, especially given the importance of this timber species in China.  Do the plots contain remeasurements?  If so, it should not be too difficult to construct dominant height equations and basal area prediction/projection equations.

 Line 138:  > 65%.  So, these are not pure larch plantations, but rather contain a considerable mixture of species.

Line 160:  Based on the tree biomass models and associated tree species, individual biomass components (tree stem, branch, leaf, and root) and total biomass (the sum of root, stem, branch, and needle) were calculated.  The authors must cite the source and reveal the individual-tree model formulation.  I am assuming that these individual-tree models do not contain any precipitation or temperature variables.

 Line 166.  It is my belief that Eq. (1) is superior to models M1 - M4.  The stand-level models convey no information about mixture of species.  At least Eq. (1) is species specific.  Eq. (1) requires the user to measure individual tree diameters and tree heights.  The same however can be said for models M1 – M4 since there is no companion system for estimating dominant height and stand basal area.

 Line 253:  I struggle with the idea that predicted biomass of models M3 and M4 contain environmental variables when observed Bi of Eq. (1) did not apparently account for temperature and precipitation.  Could the mix of species abundance be confounded with temperature and precipitation?

 Line 335: In terms of M-3 and M-4, the parameters were positive and negative, indicating that the effects of climate variables may have a positive or negative effect on stand biomass.  All the coefficients of Table 2 are positive.  Once the typographical errors are corrected, it would be beneficial if the authors explain the cause and effect of the precipitation and temperature effects on wood density and dry weight.

 Line 355.  Once again, the authors are discussing positive and negative coefficients.  Where in the manuscript?  Not Table 2.

Author Response

Dear Respected Reviewers,

Please find our response and the revised manuscript in the attached file.

Thank you very much.

Best regards,
Authors
Surya Bagus Mahardika 
Shidong Xin 
Weifang Wang 
Lichun Jiang

Author Response File: Author Response.docx

Reviewer 2 Report

Dear Authors,

Please find my comments in the attached file.

Regards

Comments for author File: Comments.pdf

Author Response

Dear Respected Reviewers,

Please find our response and the revised manuscript in the attached file.

Thank you very much.

Best regards,
Authors
Surya Bagus Mahardika 
Shidong Xin 
Weifang Wang 
Lichun Jiang

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

Dear Authors,

Thank you for taking my comments into accout.

Yet please take close look to two following issues:

line 140-please add the number of trees measured per plot.

Second in figure 2 for me it is not clear to which models presented figures refers.

Regards

 

Author Response

Dear Respected Reviewers,

Please find our response and the revised manuscript in the attached file.

Thank you very much.

Best regards,
Authors
Surya Bagus Mahardika 
Shidong Xin 
Weifang Wang 
Lichun Jiang

Author Response File: Author Response.docx

Back to TopTop