Variations in Sap Flux Density of Three Urban Tree Species and Their Main Environmental Influencing Factors in Different Timescales in the Beijing Metropolitan Area

Round 1

Reviewer 1 Report

Dear authors,

Please, find the file attached.

Kind regards.

Comments for author File: Comments.pdf

Author Response

Author Response File: Author Response.doc

Reviewer 2 Report

The authors analyzed the variation of sap flow density and its response to environmental conditions among three tree species based on detailed data (2008-2016), but their data analysis was relatively simple and the study lacked substantial innovation on the whole. Thus, I recommend major revision before it is finally accepted for publication.

1. Title: The authors claimed that they want to estimate the differences of transpiration among three tree species, but in fact, they compared the variation of sap flow density. The sap flow density and transpiration were different. High sap flow density does not mean high transpiration (or water consumption), because it also depends on sapwood area. Therefore, the authors should calculate the transpiration based on the observed sap flow density and sapwood area, and then compared their differences.

2. Abstract: The authors should condense the important results to Abstract, and the explanation of the study results should not appear in the Abstract, e.g., L30-L32.

3. Introduction: L110: If the authors explore the difference of stand transpiration among three tree species, they should describe the stand characteristics in Method section, such as plot size, age of each tree species, canopy density, stand density, mean DBH, mean tree height, and proportion of three tree species. Additionally, they should also give the method of calculating stand transpiration based on the transpiration (or sap flow density) of sample trees. 

4. Methods: Table 1, the authors should provide the detailed information of each sample tree, rather than just giving an average value. Additionally, according to the sapwood area and DBH of Robinia pseudoacacia in Table 1, the mean sapwood depth of sample trees is only about 11 mm, while the length of the sap flow probe used in this study is 30 mm. Will this lead to low measurement value in sap flow density? 

5. Results:

(1) Section 3.1: Environmental conditions during the study period should be introduced first in this section.

(2) Section 3.2: The response relations of transpiration (or sap flow density) to many environmental factors (e.g., radiation, VPD, soil moisture, etc.) are non-linear. The authors developed the sap flow equations/models coupling with the impacts of multiple factors using the multivariate linear regression. Although the fitting accuracy seems good, equations/models lack biophysical mechanism. The authors should determine the response relations of transpiration to single factor (e.g., radiation, VPD, and soil moisture) first, then develop the transpiration models coupling with the impacts of multiple factors based on Jarvis-Stewart equation/model (Whitley et al., 2008; Wang et al., 2020; Yu et al., 2021) to evaluate the different impacts of environmental conditions on transpiration among three tree species.

References:

[1] Whitley et al., 2008. A modified Jarvis-Stewart model for predicting stand-scale transpiration of an Australian native forest. Plant and Soil 305, 35–47

[2] Wang et al., 2020. Improving the Jarvis-type model with modified temperature and radiation functions for sap flow simulations. Journal of Hydrology, 587, 124981

[3] Yu et al., 2021. Assessing the impact of soil moisture on canopy transpiration using a modified Jarvis-Stewart model. Water, 13(19), 2720

6. Conclusion: The conclusion is too long. Please further refine.

Author Response

Author Response File: Author Response.doc

Round 2

Reviewer 2 Report

Section 3.3 and 3.4: The logic in analyzing the impacts of various environmental conditions on the sap flux density among three tree species at different timescales is still confused. The authors should first determine the main factors affecting the sap flux density at different timescales, e.g., partial correlation, and then, develop the sap flow density models coupling the impacts of main factors based on the determined main factors at different timescales. For example, at the daily scale, the model can be developed based on the Jarvis-Stewart equation/model because the relations between the sap flux density factors and influencing factors (e.g., VPD, radiation) are nonlinear; at seasonal and interannual scales, the models may be developed by the multiple regression equation. Therefore, I suggest that the authors further sort out the logical expression and presentation of these sections.

Author Response

Thanks for your suggestion. Section 3.3 and 3.4 were reorganized in the revised manuscript (L345-407).