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Effects of Stand Structure and Topography on Forest Vegetation Carbon Density in Jiangxi Province

Forests 2021, 12(11), 1483; https://doi.org/10.3390/f12111483

by Changshun Zhang¹

, Qinghua Deng², Aibing Liu², Chunlan Liu^3,* and Gaodi Xie¹

Reviewer 1: Anonymous

Reviewer 2: Anonymous

Reviewer 3: Anonymous

Forests 2021, 12(11), 1483; https://doi.org/10.3390/f12111483

Submission received: 26 August 2021 / Revised: 11 October 2021 / Accepted: 12 October 2021 / Published: 29 October 2021

(This article belongs to the Section Forest Ecology and Management)

Round 1

Reviewer 1 Report

The article entitled " Effects of Stand Structure and Topography on Forest Vegetation Carbon Density in Jiangxi Province" presents very interesting data collected in a very reliable and methodical manner. Potentially, the material collected provides a basis for very interesting analyses. Unfortunately, in its present form, it shows several shortcomings that should be corrected.

The authors do not address what they mean by stand structure. It is a very broad concept that covers a wide range, so it would be good to define it in the Introduction chapter,
The methodology chapter should be more detailed on how the parameters that characterize the plot and the measured trees were determined. For example, what are the basic information of the stand, how slope was measured, how canopy density was measured, how tree height was measured, how decomposition state of deadwood was determined, what are the other factors? How was the moisture content determined? How were the models between biomass and DBH calculated? What does it mean, that biomass of shrubs and deadwood was determined by harvest method? How was the biomass density (Bi) calculated?
The statistical methods are not adequately described. What post hoc tests were used for multiple comparisons, how was the p-value for posthoc tests determined? Most of the parameters are highly skewed, so it is likely that the distribution is not normal, and variances are not homogenous. If it is thru then the analysis o variance is not a first choice statistical method to use. How was the correlation calculated?
In many places, the analyses performed and the related discussion are trivial and the results obtained are quite obvious. For example, the relationship found between carbon density and abundance, breast height, tree height density, the basal area is quite obvious. Carbon density depends on the amount of wood produced, we can determine the amount of production by the volume of wood or its weight. A larger volume of wood weighs more and contains more carbon. It also has more energy expressed, for example, in joules. The volume of wood, its biomass or mass of carbon show the yield of wood only expressed in different units, so the correlation between them is obvious, just like the correlation between biomass or carbon density and dendrometry measures that are commonly used in forestry to determine the wood volume per hectare (such as DBH, BA, H, etc.). I do not deny this correlation and its practical importance, I just want to say that it is obvious and does not show any special phenomenon. Notice the similarity of the formulas in Table 1 and the general idea of the Denzin formula for tree volume.
Very interesting is the difference found in carbon density in different forest types and under different habitat conditions (altitude, slope). It seems very interesting to ask whether there are interactions between forest type and environmental conditions or characteristics of the forest itself e.g. different age or origin or altitude. It might be worth checking this using multivariate analysis of variance (if the conditions for using ANOVA are not violated) or using nonparametric methods

More detailed remarks are given below.

Line 89-91. What is the difference between wooded area, forest area, and arbor forest area? A short definition should be given.

Line 92-95. All forest type abbreviations should be introduced at once.

Line 101-102. What are the young forests, middle-aged forests, and near mature and overmature forests?

Line 104. Reference about random stratified sampling should be given.

Line 118. “The average standard plant” do authors mean tree? If so what is the decomposition status? If it was a tree, how was it weighted?

Line 123-124. What is the difference between this line and line 118-120?

Line 161 “wood” do authors mean tree?

Line 195-197. It is a comment, not a result. What’s more, it is not proved here by any means.

Table 8, Table 9. Is Total the same as Community in table 6 and 5?

Author Response

Thank you very much for taking time out of your busy schedule to review our manuscript and put forward some valuable revision suggestions. We have been carefully revised this manuscript strictly according to your suggestions. Please refer to the revised draft for specific modification results.

The authors do not address what they mean by stand structure. It is a very broad concept that covers a wide range, so it would be good to define it in the Introduction chapter。

Reply: Thank you for your good advice, and the definition of “stand structure” has been described at the end of the introduction chapter as “The stand structure in this study refers to the traditional stand characteristic factors such as stand density (SD), average diameter at breast height (ADBH), average tree height (AH), canopy density (CD) and volume per unit area (VPUA) and basal area at breast height per unit area (BA).”

The methodology chapter should be more detailed on how the parameters that characterize the plot and the measured trees were determined. For example, what are the basic information of the stand, how slope was measured, how canopy density was measured, how tree height was measured, how decomposition state of deadwood was determined, what are the other factors? How was the moisture content determined? How were the models between biomass and DBH calculated? What does it mean, that biomass of shrubs and deadwood was determined by harvest method? How was the biomass density (Bi) calculated?

Reply: Thank you for your valuable advice, and the measurement method and calculation method of each parameter has been detailed in the revised draft in methodology chapter. In order to address to this comment clearly, the following text excerpted from the revised article is the answers to the questions mentioned in this comment.

Q: What are the basic information of the stand?

Reply: Because there are too many tables this manuscripts, we did not listed it. And the basic information of the stands were as follows.

Forest types	mean altitude	Mean tree height	Mean DBH	Tree density	Mean canopy density	Mean slope degree
evergreen broad-leaved forest	340.49	8.65	12.18	1284.05	0.60	24.59
P. massoniana forest	190.91	7.72	12.58	917.15	0.49	17.06
C. lanceolata forest	333.93	8.22	11.33	1552.09	0.63	24.68
Other coniferous forest	357.06	8.72	12.28	1289.97	0.59	19.82
Mixed broadleaf-conifer forest	316.63	8.22	10.53	1691.97	0.63	23.33

Q：How slope was measured, how canopy density was measured, how tree height was measured?

Reply：Slope was measured by slope meter, canopy density by visual method and tree height by laser altimeter.

Q: How decomposition state of deadwood was determined, what are the other factors?

A: decomposition state should be determined firstly according to the method recommended by Rouvinen et al. (2002). The elevation, longitude, latitude and azimuth of the central point of each plot were measured by portable GPS instrument, the slope degree was measured by slope instrument, and the stand type, slope position and canopy density were determined by traditional community investigation method.

Q：How was the moisture content determined?

Reply：The moisture content was determined by oven method, that is, baking at 105℃ to constant weight and then weighing.

Q: How were the models between biomass and DBH calculated? What does it mean, that biomass of shrubs and deadwood was determined by harvest method? How was the biomass density (Bi) calculated?

Reply：Models between total biomass and DBH of individual trees was calculated the Existing literatures listed in the table. Shrub biomass was obtained by mean sample shrub method + harvest method. The biomass of snags and logs under 4-5 decomposition states was calculated using mean sample shrub method + harvest method. The biomass density is equal to the biomass in corresponding layer each plot is divided by the plot area (800m²) multiplied by 10000 (a ha).

The statistical methods are not adequately described. What post hoc tests were used for multiple comparisons, how was the p-value for posthoc tests determined? Most of the parameters are highly skewed, so it is likely that the distribution is not normal, and variances are not homogenous. If it is thru then the analysis o variance is not a first choice statistical method to use. How was the correlation calculated?

Reply: Thank you for your good advice, and we did a homogeneity test before ANOVA. If the significance of the homogeneity test was greater than 0.05, ANOVA and multiple comparison (LSD method) were directly carried out. Otherwise, ANOVA and multiple comparison (Tamhane method) were carried out using unassumed homogeneity, and the p-value for posthoc tests was specified in ANOVA and multiple comparison tables in the revised draft.

In many places, the analyses performed and the related discussion are trivial and the results obtained are quite obvious. For example, the relationship found between carbon density and abundance, breast height, tree height density, the basal area is quite obvious. Carbon density depends on the amount of wood produced, we can determine the amount of production by the volume of wood or its weight. A larger volume of wood weighs more and contains more carbon. It also has more energy expressed, for example, in joules. The volume of wood, its biomass or mass of carbon show the yield of wood only expressed in different units, so the correlation between them is obvious, just like the correlation between biomass or carbon density and dendrometry measures that are commonly used in forestry to determine the wood volume per hectare (such as DBH, BA, H, etc.). I do not deny this correlation and its practical importance, I just want to say that it is obvious and does not show any special phenomenon. Notice the similarity of the formulas in Table 1 and the general idea of the Denzin formula for tree volume.

Reply: Thank you for your comment and I agree that the correlation is not that special, but it is of practical importance in my study. My reason is that the method of biomass estimation from forest community volume was the most frequently used method in computing forest vegetation carbon storage and carbon density at national, provincial and even county scales in China on the basis of the same biomass-stock model for the same types of forests, however, due to the significant spatial heterogeneity of forest vegetation types, forest structure and forest quality in China, it is certainly not applicable to use the same biomass-stock model to estimate carbon storage and carbon density in different regions. Therefore, in order to estimate the vegetation carbon storage and carbon density of regional forest more accurately, it is necessary to explore the quantitative relationship between carbon density/biomass and carbon stock of main forest types in the region and that is why we carried out this study to provide a local accounting method for forest vegetation carbon density calculation for Jiangxi Province.

The unitary volume equations of different areas in Jiangxi province were used for the volume computed, and there are some differences between those models and biomass equations.

Tree species	Districts	Unary volume equation
C. lanceolata	South of Jiangxi Province	V=(0.000058061860(0.10945+0.97432D)^1.9553351)((28.3826+(-645.2923/((0.10945+0.97432D）+20)))^0.89403304)
	Jinggangshan district	V=(0.000058061860(0.10945+0.97432D)^1.9553351)((53.6998+(-3389.5577/((0.10945+0.97432D）+63)))^0.89403304)
	Mufushan district	V=(0.000058061860(0.10945+0.97432D)^1.9553351)((37.26899+(-1136.5695/((0.10945+0.97432D）+28)))^0.89403304)
	XinJiang and Le an River district	V=(0.000058061860(0.10945+0.97432D)^1.9553351)((37.5221+(-1388.5695/((0.10945+0.97432D）+35)))^0.89403304)
	Fuhe district	V=(0.000058061860(0.10945+0.97432D)^1.9553351)((33.8504+(-1020.9832/((0.10945+0.97432D）+29)))^0.89403304)
P. massoniana	South of Jiangxi Province	V=(0.000062341803(0.34879+0.96410D)^1.8551497)((41.1547+(-2277.2073/(((0.34879+0.96410D）+57)))^0.95682492)
	Jinggangshan district	V=(0.000062341803(0.34879+0.96410D)^1.8551497)((47.2481+(-2975.1142/(((0.34879+0.96410D）+63)))^0.95682492)
	Mufushan district	V=(0.000062341803(0.34879+0.96410D)^1.8551497)((35.5685+(-944.3192/(((0.34879+0.96410D）+23)))^0.95682492)
	XinJiang and Le an River district	V=(0.000062341803(0.34879+0.96410D)^1.8551497)((40.0347+(-1416.1801/(((0.34879+0.96410D）+32)))^0.95682492)
	Fuhe district	V=(0.000062341803(0.34879+0.96410D)^1.8551497)((74.3141+(-7620.0166/(((0.34879+0.96410D）+102)))^0.95682492)
Broadleaf trees	South of Jiangxi Province	V=(0.000050479055(0.29814+0.96370D)^1.9085054)((32.5420+(-1152.7459/(((0.29814+0.96370D）+37)))^0.99076507)
	Jinggangshan district	V=(0.000050479055(0.29814+0.96370D)^1.9085054)((34.2245+(-1331.0611/(((0.29814+0.96370D）+41)))^0.99076507)
	Mufushan district	V=(0.000050479055(0.29814+0.96370D)^1.9085054)((37.8524+(-1241.7049/(((0.29814+0.96370D）+31)))^0.99076507)
	XinJiang and Le an River district	V=(0.000050479055(0.29814+0.96370D)^1.9085054)((46.3460+(-2374.4336/(((0.29814+0.96370D）+51)))^0.99076507)
	Fuhe district	V=(0.000050479055(0.29814+0.96370D)^1.9085054)((30.4809+(-1070.7755/(((0.29814+0.96370D）+36)))^0.99076507)

Very interesting is the difference found in carbon density in different forest types and under different habitat conditions (altitude, slope). It seems very interesting to ask whether there are interactions between forest type and environmental conditions or characteristics of the forest itself e.g. different age or origin or altitude. It might be worth checking this using multivariate analysis of variance (if the conditions for using ANOVA are not violated) or using nonparametric methods。

Reply: Your ideas are absolutely correct and enlightening The data of forest resources, such as stand type, canopy density and age group, were mainly considered in the setting of the sample plot for national continuous forest inventory, and to ensure that the spatial distribution of the plots is even, as a result, some forest types are missing in some terrain factor gradients. Therefore, it violates the conditions for using ANOVA. We will fully adopt your suggestions in the future study of forest vegetation carbon density.

More detailed remarks are given below.

Line 89-91. What is the difference between wooded area, forest area, and arbor forest area? A short definition should be given.

Reply: Thank you very much. It's a bit of a mess here. Wooded area (forestry land) include arbor woodland, bamboo woodland, shrubby woodland, open forestland, cutting sites, burned sites, unformed forest lands, nursery sites and suitable forests as planned by the people's governments at and above the county level. Forest area include arbor forestland, bamboo forestland and specially designated irrigation forestland. Arbor forest is the forest dominated by tree species. According to the species composition, the arbor forests in Jiangxi province mainly include coniferous forests dominated by Cunninghamia lanceolata and Pine sp. forests, broadleaved forests dominated by oak, liquidambar sweetgum and schima superba forests and mixed coniferous and broadleaved forests.

The above definitions have been added in the revised draft in introduction.

Line 92-95. All forest type abbreviations should be introduced at once.

Reply: Thank you for your good advice, and we have followed your advice in this revised draft. Please refer to the Study area for the revisions.

Line 101-102. What are the young forests, middle-aged forests, and near mature and overmature forests?

Reply: It would be more appropriate to use young forest, middle forest, near-mature forest, mature forest and over-mature forest, which was determined according to the dominant tree species name and stand age.

Line 104. Reference about random stratified sampling should be given.

Reply: Thank you for your good advice, and we have given the reference in the revised manuscript, Please refer to Field survey and sampling for the revisions.

Line 118. “The average standard plant” do authors mean tree? If so what is the decomposition status? If it was a tree, how was it weighted?

Reply: Here it means average standard snag, and the snag decomposition status was determined using the method recommended by Rouvinen et al. And for snags of decay class 4 and 5, the biomass was calculated by harvesting method. And for snags of decay class 1-3, the single wood biomass model was used to calculate its biomass.

Line 123-124. What is the difference between this line and line 118-120?

Reply: Thank you for your careful review. The former is the survey of snags, and the latter is the survey of logs. We have revised it to make it more clear in the revised draft.

Line 161 “wood” do authors mean tree?

Reply: Thank you for your careful review. It means tree here and we have revised this part in the revised manuscript.

Line 195-197. It is a comment, not a result. What’s more, it is not proved here by any means.

Reply: Thank you for your careful review. We accept your suggestion and delete this content.

Table 8, Table 9. Is Total the same as Community in table 6 and 5?

Reply: Thank you very much, and the word Total is used uniformly in the revised draft.

Reviewer 2 Report

altough the manuscript is well written, it needs some deep revisions from the nomenclature point of view. Morevoer, Introduction section is very brief and flaw: the authors should increase the background of their research. For example, they didn't consider the issue of CO2 storage in general and in other parts of the world: I suggested some works to consider in they background, but they need many more. Other notes are in the attached PDF.

Comments for author File: Comments.pdf

Author Response

Thank you very much for taking time out of your busy schedule to review our manuscript and put forward some valuable revision suggestions. We have carefully revised this manuscript strictly according to your suggestions. Please refer to the revised draft for specific modification results.

1 Please, avoid to use the same words of the title: this action doesn't help the widespread of your future article. Try to use new keywords.

Reply: Thank you for your good advice, and we have used new keywords in this revised version. The keywords are stand characteristics, terrain factor, driving force and regression analysis now.

2 The Introduction section is very brief and flaw. You need to increase the background of your research. For example, you didn't consider the issue of CO2 storage in general and in other parts of the world. Due to the importance of forests in the carbon cycle, there is a vast literature that is not considered here. Furthermore, references should be made to more regions of the world to make people understand the importance of this on a planetary level. I suggest to consider the following:

1) Spampinato, G.; Malerba, A.; Calabrò, F.; Bernardo, C.; Musarella, C. Cork oak forest spatial valuation toward post carbon city by CO₂ sequestration. In New Metropolitan Perspectives; Bevilacqua, C., Calabrò, F., Della Spina, L., Eds.; NMP 2020; Smart Innovation, Systems and Technologie; Springer: Cham, Switzerland, 2021; Volume 178. https://doi.org/10.1007/978-3-030-48279-4_123

2) Karelin, D.V., Zamolodchikov, D.G., Shilkin, A.V. et al. The effect of tree mortality on CO2 fluxes in an old-growth spruce forest. Eur J Forest Res 140, 287–305 (2021). https://doi.org/10.1007/s10342-020-01330-3

However, I suggest you to consider many more.

Reply: Thank you for your valuable advice. The introduction has been revised On the basis of collecting relevant literature, the former part of the introduction is modified. The previous part of the introduction is modified as:

Forest vegetation carbon storage is the main body of terrestrial ecosystem carbon storage, which not only maintains a huge carbon pool of (550±100) Pg (1Pg=1015g), but also absorbs about 33% of the carbon emitted by human activities, playing a very important role in global carbon balance and potential carbon storage [1,2]. Since the change of forest vegetation carbon sequestration function reflects the results of forest succession, human activities and environmental changes, it is an important indicator to measure the stability and health of forest ecosystem, so the study of vegetation carbon storage becomes an important field of forest carbon storage research [3,4]. Scholars from Russia, Canada, the United States, China and other countries have studied regional or even global forest vegetation carbon storage and forest carbon cycle [5-8]. At present, the estimated global forest vegetation carbon storage is roughly 359-744 Pg [8], and the most estimated forest vegetation carbon storage for China is 17Pg in foreign materials [9]. Due to the complexity and diversity of forest types in China, it is difficult to use a unified method for estimation of forest vegetation carbon storage, and the degree of preparation of basic data varies from place to place. As a result, the estimated forest vegetation carbon storage varies significantly at national scale in China, with an average of 3.72-13.34 Pg [9-11]. Therefore, a bottom-up approach is necessary for more accurate estimation of forest vegetation carbon storage, that is, carbon storage of forest ecosystems at different regional scales is first estimated, and then carbon storage of forest ecosystems at national scale is calculated [12].

3、The writing of Latin names

Reply: Thank you for your good advice. All the Latin names here have been checked and modified correctly

4、All these information must be properly referenced. Please, provide one or more references for them.

Reply: Your advice is very helpful. References have been provided now.

5、All scientific names should be reported complete with their authorship.

Reply: Thank you for your valuable advice. All scientific names have been reported complete with their authorship in the revised draft.

6、Please, try to improve these graphs: they are a little bit confused in their setting.

Reply: Thank you for your valuable advice. We have improved those graphs now in this revised manuscript.

7、Other details.

Reply: Thank you for your valuable advice, and your valuable suggestions have helped us a lot to improve the quality of this manuscript. We have revised the above details in this revised manuscript.

Reviewer 3 Report

The manuscript presents analytics information’s about Carbon storage in different forest type. Study was prepared for Jiangxi Province in Southeast China. Authors have targeted on evaluation of carbon content relations between forest stand structure and topography. I consider this topic as relevant, very interesting, and actual demanded.

I have to presented work next comments and recommendations:
I have restrictions to used scientific terminology. I recommend change some presented words or collocations:
Carbon density – carbon storage, content, volume
Arbor forest (?) – Forest (all forest naturally contain trees)
Arbor tree - tree
main collective forest region – region with huge forest density
unit area stock – Growing stock in forest unit
organ – element, component
community (table 3, 5,6 ) - total

Row 53-54:

If total forest area in Jiangxi region represents 10.799 mil. hectares and create share 64.69%, I calculate total land area as 16.624 mil. hectares. Arbor (?) forests with 8,085 mil. hectares don´t create 74,87% of total land area.

In chapter Material and Methods between basal data I lack of altitude or elevations information’s in analysed forests. Please, append this.
Append too explanation for shadow colour in Figure 1. Is it topographical map? What is shadow?
I recommend join chapter 2.2 Standard sample setting and 2.3 Sample plot investigation (?).

Specify shape of standard plot – I thionk it is rectangular square. If authors have selected 211 forest subcompartments, how many subcompartments were in Study area total? Please append.

Row 113-114

How were measured information’s about slope and canopy density? Only visually estimation?

Whereupon authors investigated names of dominant trees, whenever all trees with diameter about 5 cm on plots were measured? Dominant tree species can objective calculated.

What is “average standard plant?” Average is only calculated (virtual?) value, plant express real value.

How were measured diameters of fallen deadwood? In centre or end of divided section? How many decomposition status (decay classes) were used? How were different decay classes describe?

If shrub was consider as diameter under 5 cm, young tree individuals were consider as shrubs, not trees? It is correct?
How was measured carbon content in herb layer, litter layer and deadwood? I think that authors presents in Table 2 only carbon concentration in tree biomass by different forest types, not real technique. How kind of biomass was measured by trees and shrubs – aboveground or total with belowground? I think that only abovegroud, this fact must be highlighted.

Authors haven’t surveyed Carbon in soil, I recommend naturally join litter with soil (anorganic material) instead joining with trees, shrubs, herbs and deadwood (organic material)
I disagree with declaration, that “forest plots were mainly distributed in the area below 311.68m,” and “plot was mainly distributed in the steep slope area above 22.73° (Table 4)”. Presented values are accurately average values. To relevant argumentation, I need append histograms or tables with class distribution of elevation and slope of all plots. Please quantify how many plots with which share lies in particular classes or categories.

I think, that presented values of Standard deviations in table 3 and 4 are too lower. I suspect, that by average Volume per hectare 76 is standard deviation only 4 (and by other parameters too). Variability must be higher, see too Table 10 with comparison analysis of Carbon density surveyed by other researchers (it does not matter, by different parameters as Volume and Carbon). I judge, present values are not standard deviation but standard errors? Or?
Table 5 presents only differences in average values of carbon density, although are presented significant differences. I suspect significant differences by litter with values 0,80a and 0,81ab. I lack by each layer and category too coefficient of variability. In scientific results I need standard deviations or standard errors with ± sign. Please, append those values. Instead term “Community” use term “total”.
Subchapter 3.4.1 and 3.4.2 presents own results in same Table 7, I recommend their joining.
I lack of more presented graphs with relation of presented stand and topographic parameters. Too for histograms (categories of aspect, slope, altitude etc.).

By my opinion proposed topic is relevant, but authors must markedly improve paper quality. Authors must explain each technique by used methods from field survey to laboratory works and statistical evaluation (for each component: trees, shrubs, herbs, litter and deadwoods). I recommend improve too several results adn append some graphs.

Author Response

Detailed Modification Suggestions

Reply: Thank you for your good advice. Now the full text has been revised. Since this study is based on quadrat scale, the quadrat vegetation carbon density is equal to the quadrat vegetation carbon storage divided by the quadrat area, and volume refers to the volume per unit area in correlation analysis and regression analysis.

Arbor forest (?) – Forest (all forest naturally contain trees)

Reply: Thank you for your good advice. Now the full text has been revised, “forest area” has been replaced by “forestry land”, which including arbor forest land and bamboo forestland with canopy density above 0.2, shrub land, open forestland, cutting site, burned site, unformed forestland, nursery site and suitable forestland planned by the people's government at or above the county level used in revised draft. Arbor forest was forestry land dominated by arbor tree species.

Arbor tree – tree

Reply: Thank you for your good advice. Now the full text has been revised, “arbor layer” has been used in revised draft.

main collective forest region – region with huge forest density

Reply: Thank you for your review, here Jiangxi province is the main collective forest region. Because the forests in Jiangxi province are mainly middle and young plantations, the forest carbon density is not high.

unit area stock – Growing stock in forest unit

Reply: Thank you for your good advice, we use “volume per unit area” in this revised draft.

organ – element, component

Reply: Thank you for your good advice, we have used layer instead of “organ” in the revised manuscript.

community (table 3, 5,6 ) – total

Reply: Thank you for your good advice, “Total ” has been used in the revised draft.

Row 53-54:

If total forest area in Jiangxi region represents 10.799 mil. hectares and create share 64.69%, I calculate total land area as 16.624 mil. hectares. Arbor (?) forests with 8.085 mil. hectares don´t create 74,87% of total land area.

Reply: Thank you very much for your careful review. We did make a mistake. “total forest area in Jiangxi region represents 10.799 mil. hectares and create share 64.69%,……Arbor forests with 8.085 mil. hectares don´t create 74,87% of total land area.” should be “total forestry land area in Jiangxi region represents 10.799 mil. hectares and create share 64.69%, ……Arbor forests with 8.085 mil. Hectares, accounting for about 74.87% of the total forestry land area.”. We have corrected it in the revised manuscript.

In chapter Material and Methods between basal data I lack of altitude or elevations information’s in analysed forests. Please, append this.

Reply: Thank you for your valuable advice. The measurement and calculation methods of each index have been introduced in detail in the revised draft.

Append too explanation for shadow colour in Figure 1. Is it topographical map? What is shadow?

Reply: Thank you for your careful review, shadow colour in Figure 1 is the elevation gradient change diagram, and its legend has been shown in the revised draft.

I recommend join chapter 2.2 Standard sample setting and 2.3 Sample plot investigation (?).

Reply: Thank you for your valuable suggestion, we have joined them in the revised draft.

Specify shape of standard plot – I think it is rectangular square. If authors have selected 211 forest subcompartments, how many subcompartments were in Study area total? Please append.

Reply: You are right. There's something wrong with the representation, it should be “the 28.28 m* 28.28 m forest continuous inventory sample plots, and there are about 2600 forest continuous inventory sample plots in Jiangxi Province.

Row 113-114

How were measured information’s about slope and canopy density? Only visually estimation?

Reply: Thank you very much for your careful review. Slope degree was measured by slope meter, azimuth was measured by GPS meter, slope position was estimated according to plot position, and canopy density was estimated by the investigator empirically. All these have been specified in the revised draft.

Whereupon authors investigated names of dominant trees, whenever all trees with diameter about 5 cm on plots were measured? Dominant tree species can objective calculated.

Reply: Thank you very much for your careful review. There's some wrong with the representation. For pure forest, the dominant tree species can be seen obviously, while for mixed forest, the dominant tree species can be determined on the bases of the dominance degree, importance value or stock proportion of each tree species calculated on the tree survey data in the sample plot. And this section has now been modified to be more specific.

What is “average standard plant?” Average is only calculated (virtual?) value, plant express real value.

Reply: You are right. There's some wrong with the representation. It has been changed into the average standard shrub, average standard snag, average standard log and other specific objects. The average standard plant was determined by the values of DBH, H, crown breadth.

How were measured diameters of fallen deadwood? In centre or end of divided section? How many decomposition status (decay classes) were used? How were different decay classes describe?

Reply: You are right. For fallen deadwood (logs), the log length, the maximum diameter (dmax) and the minimum diameter (dmin) were determined in order to compute the log volume . Then the method of Rouvinen et al. was used to determine the decomposition state of logs, and the fresh weight was firstly weighed using the harvesting method, then 500g samples of each decomposition state were collected and taken back to determine the moisture content. All have been modified to be more specific and clear in the revised manuscript.

If shrub was consider as diameter under 5 cm, young tree individuals were consider as shrubs, not trees? It is correct?

Reply: Thank you for your good advice. For shrub, the shrubs with DBH < 5cm and height ≥50cm were investigated, for young tree individuals, if its height ＜50cm，it will be regarded as herb. Otherwise, it will be regarded as shrub.

How was measured carbon content in herb layer, litter layer and deadwood? I think that authors presents in Table 2 only carbon concentration in tree biomass by different forest types, not real technique. How kind of biomass was measured by trees and shrubs – aboveground or total with belowground? I think that only abovegroud, this fact must be highlighted.

Reply: Thank you for your good advice. We did not determine the carbon content of each component of trees, shrubs, herbs, snags, logs and litters, and their carbon contents of each component were mainly referenced from the existing literature data. The carbon content of each component and its references have been clearly listed in Table 2. The biomasses involved in this study were total biomasses. And the tree biomass (aboveground biomass and underground biomass) was calculated using single wood biomass model, shrub biomass was computed using standard strains + harvest method, herb biomass and litter biomass calculated using harvesting method, snag and log biomass (belong to 1-3 decomposition state) was computed using the single wood biomass model, and the biomass of 4-5 grade of decomposition state was calculated using the Mean standard strain + harvest method. The above contents have been specified in the revised draft.

Authors haven’t surveyed Carbon in soil, I recommend naturally join litter with soil (anorganic material) instead joining with trees, shrubs, herbs and deadwood (organic material)

Reply: Thank you for your good advice. Due to the large number of forest plots, we only collected soil samples from 60 forest plots, and the test analysis of soil samples has not been completed. We will carry out our research in the relationships between soil carbon and vegetation carbon in our following study.

I disagree with declaration, that “forest plots were mainly distributed in the area below 311.68m,” and “plot was mainly distributed in the steep slope area above 22.73° (Table 4)”. Presented values are accurately average values. To relevant argumentation, I need append histograms or tables with class distribution of elevation and slope of all plots. Please quantify how many plots with which share lies in particular classes or categories.

Reply: Thank you very much for your careful review. We made the modification according to your suggestion. Please refer to 3.2 Descriptive statistics of stand structure and topographyfor the revisions.

Reply: Thank you for your careful review, you are right. We confirm that the values of line CD in Table 3 and Table 4 are standard errors rather than standard deviations, and the standard deviation values are filled in the corresponding tables in the revised draft.

Table 5 presents only differences in average values of carbon density, although are presented significant differences. I suspect significant differences by litter with values 0.80a and 0.81ab. I lack by each layer and category too coefficient of variability. In scientific results I need standard deviations or standard errors with ± sign. Please, append those values. Instead term “Community” use term “total”.

Reply: Thank you for your good advice. It has been modified according to your suggestion. There is no significant difference between litter with 0.80 and 0.81 because they have a same letter “a”.

Subchapter 3.4.1 and 3.4.2 presents own results in same Table 7, I recommend their joining.

Reply: Thank you for your good advice. We have combined them in the revised draft.

I lack of more presented graphs with relation of presented stand and topographic parameters. Too for histograms (categories of aspect, slope, altitude etc.).

Reply: Thank you for your good suggestion. It has been modified as you suggested, and the corresponding chart or table has been added.

Reply: Thank you for your good advice. It has been modified according to your suggestion, Each technique has been explained by used methods from field survey to laboratory works and statistical evaluation, such as the elevation, longitude, latitude and azimuth of the central point of each plot were measured by portable GPS instrument, the slope degree was measured by slope instrument. The corresponding charts and tables such as Fig. 2 and Table 11 have been added in the revised manuscript.

Round 2

Reviewer 1 Report

The manuscript has been substantially revised and with minor changes may be published in the journal Forests.

I suggest adding table with characteristic of stand examined to supplementary materials

I suggest adding at the end of Field survey and sampling section the following information: The moisture content in deadwood, plants and litter was determined by oven method, that is, baking at 105℃ to constant weight and then weighing.

Line 460 – 463. There are simpler and more direct methods to prove that forests are young. I think that the main message of that sentence is different. I suggest to rephrase it to be more precise.

In the answer to the review authors wrote “forest community volume was the most frequently used method in computing forest vegetation carbon storage and carbon density at national, provincial and even county scales in China on the basis of the same biomass-stock model for the same types of forests, however, due to the significant spatial heterogeneity of forest vegetation types, forest structure and forest quality in China, it is certainly not applicable to use the same biomass-stock model to estimate carbon storage and carbon density in different regions. Therefore, in order to estimate the vegetation carbon storage and carbon density of regional forest more accurately, it is necessary to explore the quantitative relationship between carbon density/biomass and carbon stock of main forest types in the region and that is why we carried out this study to provide a local accounting method for forest vegetation carbon density calculation for Jiangxi Province.” In my opinion that are very important statement. I propose to shorten it a bit and use in the conclusions or discussion section or in the introduction section as part of the study goal.

Author Response

I suggest adding table with characteristic of stand examined to supplementary materials

Reply: Thank you for your valuable advice. We have added a table about the characteristics of the stands examined in the revised draft.

Table 1 Characteristics of experimental stands （Value±SD）

Stands	Number of plots (n)	Average altitude (m)	AH (m)	ADBH (cm)	TD (n/ha)	CD (-)	Slope degree (°)
EBF	81	340.49±271.33	8.65±2.83	12.18±4.07	1284.05±726.83	0.60±0.19	24.59±12.54
PMF	33	190.91±137.96	7.72±2.54	12.58±4.27	917.15±556.90	0.49±0.17	17.06±12.82
CLF	28	333.93±323.88	8.22±1.86	11.33±2.56	1552.09±839.47	0.63±0.15	24.68±8.91
OCF	17	357.06±450.97	8.72±2.78	12.28±3.15	1289.97±137.73	0.59±0.14	19.82±9.93
MBCF	52	316.63±231.81	8.22±2.49	10.53±2.42	1691.97±927.17	0.63±0.16	23.33±11.09

Note: EBF, Evergreen broadleaf forests; PMF, P. massoniana forest; CLF, C. lanceolata forest; OCF, Other coniferous forest; MBCF, Mixed broadleaf-conifer forest. The same below.

I suggest adding at the end of Field survey and sampling section the following information: The moisture content in deadwood, plants and litter was determined by oven method, that is, baking at 105℃ to constant weight and then weighing.

Reply: Thank you for your valuable advice. We have added it at the end of the part of field survey and sampling in the revised draft.

Line 460 – 463. There are simpler and more direct methods to prove that forests are young. I think that the main message of that sentence is different. I suggest to rephrase it to be more precise. The modification result is as follows:

Reply: Thank you for your valuable advice. We have revised it as you suggestion in the revised draft.

The average FVCD of Jiangxi province was 44.23 Mg/ha in, far lower than the average level of FVCD in the world, which proved that the forest in Jiangxi province was dominated by middle and young forests with low carbon density, and also indicated that the potential of forest vegetation carbon storage in Jiangxi province was huge.

Reply: Thank you for your valuable advice. We have added a table about the characteristics of the stands examined in the revised draft.

Reviewer 3 Report

Authors make changes in the paper and final quality is improved. I have been satisfied with this version.

Author Response

Detailed Modification Suggestions

Arbor forest (?) – Forest (all forest naturally contain trees)

Arbor tree – tree

Reply: Thank you for your good advice. Now the full text has been revised, “arbor layer” has been used in revised draft.

main collective forest region – region with huge forest density

unit area stock – Growing stock in forest unit

Reply: Thank you for your good advice, we use “volume per unit area” in this revised draft.

organ – element, component

Reply: Thank you for your good advice, we have used layer instead of “organ” in the revised manuscript.

community (table 3, 5,6 ) – total

Reply: Thank you for your good advice, “Total ” has been used in the table 2, 5 6,7 8 in the revised draft.

Row 53-54:

Reply: Thank you very much for your careful review. We did make a mistake. “total forest area in Jiangxi region represents 10.799 mil. hectares and create share 64.69%,……Arbor forests with 8.085 mil. hectares don´t create 74.87% of total land area.” should be “total forestry land area in Jiangxi region represents 10.799 mil. hectares and create share 64.69%, ……Arbor forests with 8.085 mil. Hectares, accounting for about 74.87% of the total forestry land area.”. We have corrected it in the revised manuscript in the third in the part of the introduction, and the results are as follows:

Jiangxi Province is the main collective forest region in south China, with rich for-est resources. According to the data of the ninth Forest Resources inventory of China, by the end of 2016, the total area of forestry land (i.e., arbor forest land and bamboo forestland with canopy density above 0.2, shrub land, open forestland, cutting site, burned site, unformed forestland, nursery site and suitable forestland planned by the people's government at or above the county level) in Jiangxi Province was 10,799,000 ha, accounting for about 64.69% of the total land area. Among them, the arbor forest area (dominated by arbor tree species) was 8,084,800 ha, accounting for about 74.87% of the total forestry land area. The main forest types include conifer forest dominated by Cunninghamia lanceolata (Lamb.) Hook., Pinus Massoniana Lamb., evergreen broadleaf forest and mixed conifer and broadleaf forest [16]. Although there are some reports on forest vegetation carbon storage/density in Jiangxi Province, except for a very small number of studies based on remote sensing images [17], those reports are mainly based on forest resource inventory data [18-22] or researches of typical forests (e.g., evergreen broad-leaved forest, Phyllostachys edulis (Carriere) J. Houzeau forest, C. lan-ceolata forest) in typical areas [23-27], and thus lack of research on FVCD and its driving forces based on systematic distribution at provincial scale.

In chapter Material and Methods between basal data I lack of altitude or elevations information’s in analysed forests. Please, append this.

Reply: Thank you for your valuable advice. We have added a table about stands in the revised draft.

Table 1. Characteristics of experimental stands （Value±SD）

Stands	Number of plots (n)	Average altitude (m)	AH (m)	ADBH (cm)	TD (n/ha)	CD (-)	Slope degree (°)
EBF	81	340.49±271.33	8.65±2.83	12.18±4.07	1284.05±726.83	0.60±0.19	24.59±12.54
PMF	33	190.91±137.96	7.72±2.54	12.58±4.27	917.15±556.90	0.49±0.17	17.06±12.82
CLF	28	333.93±323.88	8.22±1.86	11.33±2.56	1552.09±839.47	0.63±0.15	24.68±8.91
OCF	17	357.06±450.97	8.72±2.78	12.28±3.15	1289.97±137.73	0.59±0.14	19.82±9.93
MBCF	52	316.63±231.81	8.22±2.49	10.53±2.42	1691.97±927.17	0.63±0.16	23.33±11.09

Note: EBF, Evergreen broadleaf forests; PMF, P. massoniana forest; CLF, C. lanceolata forest; OCF, Other coniferous forest; MBCF, Mixed broadleaf-conifer forest. The same below.

Fig. 2 Variation characteristics of plot quantity with altitude gradients and slope gradients

Append too explanation for shadow colour in Figure 1. Is it topographical map? What is shadow?

Reply: Thank you for your careful review, shadow colour in Figure 1 is the elevation gradient change diagram, and its legend has been shown in the revised draft. Figure 1 was as follows in the revised draft.

Fig. 1 Distribution of forest continuous inventory sample plots on the topographical map of Jiangxi province

I recommend join chapter 2.2 Standard sample setting and 2.3 Sample plot investigation (?).

Reply: Thank you for your valuable suggestion, we have joined them in the revised draft. And now name of 2.2 section is Field survey and sampling in the revised draft.

Specify shape of standard plot – I think it is rectangular square. If authors have selected 211 forest subcompartments, how many subcompartments were in Study area total? Please append.

Row 113-114

How were measured information’s about slope and canopy density? Only visually estimation?

Whereupon authors investigated names of dominant trees, whenever all trees with diameter about 5 cm on plots were measured? Dominant tree species can objective calculated.

After the standard plot was set up, the following investigations were undertaken. (1) The basic information of the standard plot was investigated, the elevation, longitude, latitude and azimuth of the central point of each plot were measured by portable GPS instrument, the slope degree was measured by slope instrument, and the stand type, slope position and canopy density were estimated by traditional community investigation method. (2) All the living trees (diameter at breast height (DBH) ≥5cm and height 5 m) and snags in the sample plot were measured. The DBH was measured with girth diameter ruler, the tree height were measured using the laser altitometer, and the name, DBH and tree height of each standing tree (living trees and snages) were recorded. For each snag, decomposition state should be determined firstly according to the method recommended by Rouvinen et al. [31], then an average standard snag for decay class 4 and 5 should be selected and cut down, and the fresh weight of each organ should be weighed, then about 500g samples of each organ was collected in order to determine the moisture content. (3) For logs, the log length, the DBH, the maximum diameter (dmax) and the minimum diameter (dmin) were determined in order to compute the log volume [V=πl(〖d_max〗^2+〖d_min〗^2 )/8]. Then the method of Rouvinen et al. [31] was used to determine the decomposition state of logs, then an average standard log for decay class 4 and 5 should be selected and cut down and the fresh weight was firstly weighed using the harvesting method, then 500g samples of each decomposition state were collected and taken back to determine the moisture content. (4) Three 5m*5m shrub plots were randomly established in each forest plot, and the shrubs with DBH < 5cm and height ≥50cm were investigated. The name, ground diameter, height and crown width of each shrub in a shrub plot were measured and recorded, and then three average standard shrubs in each plot were selected according to the mean values of ground diameter, height and crown width, and the fresh weight was weighed using harvest method, and then 500g samples were collected to determine its moisture content. (5) A 1m*1m herb plot was established in each shrub plot, and the name, height and coverage of each herb with height < 50cm in each herb plot were measured and recorded, and the decomposed state of litter was determined using the method recommended by Zhang et al. [32] in each herb plot, then the litters in different decomposed state were collected, and all the above-ground and underground parts of herbs in each herb plot were collected by harvesting method. The fresh weights of the litters in different decomposed state, above-ground and underground parts of herbs each plot were weighed first, and 300 g samples were taken back to determine the moisture content.

What is “average standard plant?” Average is only calculated (virtual?) value, plant express real value.

Reply: You are right. There's some wrong with the representation. It has been changed into the average standard shrub, average standard snag, average standard log and other specific objects. The average standard individual was determined by the values of DBH or ground diameter, H, crown breadth.

How were measured diameters of fallen deadwood? In centre or end of divided section? How many decomposition status (decay classes) were used? How were different decay classes describe?

Reply: You are right. For each log, the log length, the maximum diameter (dmax) and the minimum diameter (dmin) were determined in order to compute the log volume . Then the method of Rouvinen et al.[Rouvinen, S.; Kuuluvainen, T.; Karjalainen, L. Coarse woody debris in old Pinus sylvestris dominated forests along a. Canadian Journal of Forest Research 2002, 32, 2184-2200] was used to determine the decomposition state of logs, and the fresh weight was firstly weighed using the harvesting method, then 500g samples of each decomposition state were collected and taken back to determine the moisture content. All have been modified to be more specific and clear in the revised manuscript.

If shrub was consider as diameter under 5 cm, young tree individuals were consider as shrubs, not trees? It is correct?

Table 2. Carbon concentration of different forest types

Vegetable Layers	EBF	PMF	CLF	OCF	MBCF	Reference
Arbor and snag	0.5115	0.5523	0.5375	0.5431	0.5296	[38]
Shrub and litter	0.5000	0.5000	0.5000	0.5000	0.5000	[12]
Herb and snag	0.4500	0.4500	0.4500	0.4500	0.4500	[39]

Note: EBF, Evergreen broadleaf forests; PMF, P. massoniana forest; CLF, C. lanceolata forest; OCF, Other coniferous forest; MBCF, Mixed broadleaf-conifer forest. The same below.

Authors haven’t surveyed Carbon in soil, I recommend naturally join litter with soil (anorganic material) instead joining with trees, shrubs, herbs and deadwood (organic material)

Among the topographic factors, the elevation of the sample plots was positive skew distribution (Table 4), and the forest plots were mainly distributed in the altitudinal gradients 50~500 m, which was consistent with the fact that landform is dominated by low mountains and hills in Jiangxi province. The slope of the sample plot was negative deviation, and the forest sample plots were mainly distributed in the slope degree gradients 10~40 ° (Table 4 and Fig. 2).

Fig. 2 Variation characteristics of plot quantity with altitude gradients and slope gradients

Table 3. Mean, standard deviation (SD), coefficient of variation (CV), minimum, maximum, range, skewness and kurtosis of vegetation carbon density

Layers	Mean	SD	CV (%)	Minimum	Max	Skewness	Kurtosis
Arbor layer（Mg/ha）	36.00	29.71	5.68	0.61	163.51	1.54	5.91
Shrub layer（Mg/ha）	6.11	6.26	7.05	0.00	37.23	2.07	8.53
Herb layer（Mg/ha）	0.31	0.41	9.18	0.00	4.56	6.02	55.96
Litter layer（Mg/ha）	0.86	0.64	5.14	0.04	4.90	2.29	11.84
Snag and log layer（Mg/ha）	0.94	2.40	17.53	0.00	16.52	4.10	21.73
Total（Mg/ha）	44.23	31.95	4.97	2.11	177.58	1.54	5.94

Table 4. Mean, standard deviation (SD), coefficient of variation (CV), minimum, maximum, skewness and kurtosis of stand structure and topography

Indictors	Mean	SD	CV (%)	Minimum	Max	Skewness	Kurtosis
BA (m²/ha）	15.16	10.30	4.68	0.40	46.64	0.78	3.02
VPA (m³/ha）	76.01	60.73	5.50	1.07	341.26	1.20	4.58
ADBH(cm)	11.73	3.57	2.09	5.40	25.30	0.86	4.10
AH (m)	8.35	2.49	2.06	2.60	15.40	0.39	3.12
TD (n/ha)	1363.24	798.81	4.03	138.00	4938.00	1.10	4.81
CD (-)	0.59	0.18	2.05	0.20	0.95	-0.23	2.25
Elevation (m)	311.68	275.37	6.08	20.00	1800.00	2.05	9.21
Slope degree (°)	22.73	11.84	3.59	0.00	60.00	-0.10	2.57

Reply: Thank you for your good advice. It has been modified according to your suggestion. There is no significant difference between litter with 0.80 and 0.81 because they have a same letter “a”.

Subchapter 3.4.1 and 3.4.2 presents own results in same Table 7, I recommend their joining.

Reply: Thank you for your good advice. We have combined them in the revised draft.

I lack of more presented graphs with relation of presented stand and topographic parameters. Too for histograms (categories of aspect, slope, altitude etc.).

Reply: Thank you for your good suggestion. It has been modified as you suggested, and the corresponding chart or table has been added. The corresponding charts and tables such as Fig. 2 and Table 11 have been added in the revised manuscript.

Fig. 2 Variation characteristics of plot quantity with altitude gradients and slope gradients

Table 11. Relationships between forest structure and altitude and slope degree respectively

Indictors	BA	VPUA	ADBH	AH	TD	CD
Altitude	0.29**	0.31**	0.16*	0.09	0.14*	0.17*
Slope degree	0.29**	0.28**	0.18*	0.17*	0.23**	0.29**

Reply: Thank you for your good advice. It has been modified according to your suggestion, each technique has been explained by used methods from field survey to laboratory works and statistical evaluation, such as the elevation, longitude, latitude and azimuth of the central point of each plot were measured by portable GPS instrument, the slope degree was measured by slope instrument. These aspects are rewritten in the revised draft, and the specific contents were in the parts 2.1 to 2.5 in the revised draft. For example, the following is the revised field survey.
After the standard plot was set up, the following investigations were undertaken. (1) The basic information of the standard plot was investigated, the elevation, longitude, latitude and azimuth of the central point of each plot were measured by portable GPS instrument, the slope degree was measured by slope instrument, and the stand type, slope position and canopy density were determined by traditional community investigation method. (2) All the living trees (diameter at breast height (DBH) ≥5cm and height 5 m) and snags in the sample plot were measured. The DBH was measured with girth diameter ruler, the tree height were measured using the laser altitometer, and the name, DBH and tree height of each standing tree (living trees and snages) were recorded. For each snag, decomposition state should be determined firstly according to the method recommended by Rouvinen et al. [31], then an average standard snag for decay class 4 and 5 should be selected and cut down, and the fresh weight of each organ should be weighed, then about 500g samples of each organ was collected in order to determine the moisture content. (3) For logs, the log length, the DBH, the maximum diameter (dmax) and the minimum diameter (dmin) were determined in order to compute the log volume. Then the method of Rouvinen et al. [31] was used to determine the decomposition state of logs, then an average standard log for decay class 4 and 5 should be selected and cut down and the fresh weight was firstly weighed using the harvesting method, then 500g samples of each decomposition state were collected and taken back to determine the moisture content. (4) Three 5m*5m shrub plots were randomly established in each forest plot, and the shrubs with DBH < 5cm and height ≥50cm were investigated. The name, ground diameter, height and crown width of each shrub in a shrub plot were measured and recorded, and then three average standard shrubs in each plot were selected according to the mean values of ground diameter, height and crown width, and the fresh weight was weighed using harvest method, and then 500g samples were collected to determine its moisture content. (5) A 1m*1m herb plot was established in each shrub plot, and the name, height and coverage of each herb with height < 50cm in each herb plot were measured and recorded, and the decomposed state of litter was determined using the method recommended by Zhang et al. [32] in each herb plot, then the litters in different decomposed state were collected, and all the above-ground and underground parts of herbs in each herb plot were collected by harvesting method. The fresh weights of the litters in different decomposed state, above-ground and underground parts of herbs each plot were weighed first, and 300 g samples were taken back to determine the moisture content.

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Effects of Stand Structure and Topography on Forest Vegetation Carbon Density in Jiangxi Province

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