RC1

In response to the achievement of carbon neutrality target in China, Yang et al. estimated the forest biomass C storage and its changes over the past four decades and especially updated in the most recent decade. The scientific question was quite straightforward, the methods were well established, and the conclusions were reliable and robust. Although the MS is well written, there remain a few minor issues to address (see short list below). but I think these should be straightforward.

General comment:

One of my concerns is that the estimate of forest C stocks and C uptake capacity should not only focus on plant biomass but also consider soil C sequestration. Additionally, compared with other biomass estimation studies, what are the advantages and innovations of this study?

Response: Thanks for the comments. Biomass carbon is the first component of carbon cycling in forest systems, followed by litter carbon and soil organic carbon. We agree with the reviewer that soil carbon should also be included when estimating carbon sink in forest ecosystems. As showed in the title of the manuscript, however, in this study we focus on biomass carbon stocks and carbon sinks because the forest inventories are of timber volumes primarily and related directly to forest biomass. To estimate changes in soil carbon in forests, we need much more detailed information of the carbon cycling in forest ecosystems which are beyond the targets of the present study. As pointed by the reviewer, soil carbon is equally important to biomass carbon in forests, we have added brief discussion in the revision (Lines 202–207) by referencing to previously published studies of forest soil carbon.

There have been published literatures concerning national scale forest carbon of China. The estimated carbon stocks in those studies are less comparable because of the methodological differences and the databases adopted. The magnitude of carbon sink will be misleading when they were derived by comparing the estimated carbon stocks in those separated studies. In this study, we applied a method, which had been proved of the least bias, consistently over the period of all the eight national forest inventories from 1977 to 2018. The estimated carbon sequestration derived from the comprehensive databases of this study are thus of high precision and more persuasive. Additionally, the incorporation of the latest two inventories, 2009-2013 and 2014-2018, in the temporal analysis in this study revealed the significance of the planted forests and the persistence of carbon sequestration in natural forests of China. The results will be a robust baseline for further studies of forest management both on national and regional scales.

Specific comments:

From your method, you should have calculated the biomass of each province, can you add the biomass results of each province in the attached table?

Response: Thanks for your suggestion, we did calculate the biomass results of each province. The relevant data have been added to the appendix A (see Table A3 and A4).

Line 19: Density can be taken several ways, best to define this term. It is the average stock per area? May be C storage per unit area.

Response: Density is defined in the MS (Line 19) as the C pool per unit area.

Lines 21–24: The data you given here needs to be confirmed.

Response: Yes, we have confirmed.

Line 27: China’s

Response: Thanks! Yes, we did (Line 25).

Line 28: Ecological

Response: Yes, we did (Line 27).

Lines 46–48: It just is not been studied much.

Response: Yes, we did (Line 45).

Lines 107–109: Specific tables or figures should be added to show where this part of the results came from.

Response: We have added Table 1 and Figure 1 (Line 128).

Table 2: Please add the averages for 1977–2008 and 2009–2018 in the format of Table 1. And please add the corresponding content to the result section.

Response: We have supplemented the relevant data in Table 2 and added the corresponding content at Results section (Lines 148, 133–135 and 137–139).

Line 142: “The average C sink for the previous 30years was calculated by ...” Please add a space between 30 and years.

Response: Thanks! Yes, we did (Line 167).

Lines 154–158: Similar with Lines 107–109.

Response: Yes, we did (Line 182–184).

Lines 167–172: Why did Fang et al. adopt a linear relationship that makes the C sink for 1977–2003 lower than the result in this paper.

Response: Fang et al. adopted a linear relationship in early studies, where the forest C pool before 1999 were estimated significantly lower than the results in this study, making the C sink during 1997–2003 higher than our results. More detailed data can be found in Fang et al., 2007.

Reference: Fang, J., Guo, Z., Piao, S. and Chen, A.: Terrestrial vegetation carbon sinks in China, 1981–2000, Sci. China Ser. D-Earth Sci., 50, 1341–1350, 2007.

RC2

In context of climate change, comprehensively estimate of forest C stocks will be helpful for forest carbon sequestration, as well as achieving target for carbon neutrality in 2060 proposed by the Chinese government. There is a timely need for a greater global perspective in assessing carbon sequestration using datasets of eight inventory periods from 1977 to 2018. The authors highlight that the pronouncing increases in total biomass C pool and average biomass C density of Chinese forests were largely attributed to afforestation practices, forest age growth, and environmental changes. Overall, the manuscript is well written and its objectives adequately addressed in the discussion section. I do, however, also have some more detailed comments on the manuscript. My recommendation is minor revision with reassessment by the editor.

General comment:

The authors should bring out the novelty of the study. The authors should be clearer about the uniqueness of the study.

While the paper presents some useful results, does the paper present new product or new methodology compare with other related studies?

In the discussion part, a real discussion about the effects of environmental changes on total biomass C pool and average biomass C density of Chinese forests should be stated, and its relationship to other existing works. Implications (clear and striking messages) about this topic also should be required.

Response: Thanks for the suggestion of highlighting the novelty and uniqueness of the study. We have stated our response to the analogous comments of the reviewer #1. Here we’d like to address two points in this study. First, the methodological consistency over the period from 1977 to 2018 together with the comprehensive national inventory databases of forests in this study guaranteed the reliability of C uptake estimations; and second, when the contribution of reforestation/afforestation to carbon sequestration have been well perceived, the incorporation of the latest two inventories, 2009–2013 and 2014–2018, into the preceding six inventories in this study revealed the significant and persistent carbon uptake by natural forests on national scale in China, where the soil and climate conditions varied greatly in different regions. Additionally, regarding the methods, we applied the continuous expansion factor method (BEF) in our estimation, which is considered to be the most suitable method for estimating regional forest biomass C pools (Fang et al., 1998; Fang &Wang, 2001; Teobaldelli et al. 2009; Guo et al., 2010). Because the BEF method estimates biomass as a function of timber volume and thus incorporates effects of forest age, forest density and forest site quality, it can accurately estimate forest biomass of all age classes (Lines 57–66).

This temporal sequence of the estimated carbon sequestration by natural and planted forests are helpful for better understanding the importance of the national-scale reforestation and afforestation practices in China and the offset effects of forests to the anthropogenic C emissions. We also discussed the effects of environmental changes on the C uptakes by forests, though no quantifying analysis was conducted on these effects due to the data limitation. We have added the discussion in the revised manuscript (Lines 259, 268-272, 277-284).

Reference:

Fang, J., Wang, G., Liu, G., and Xu, S.: Forest biomass of China: An estimate based on the biomass-volume relationship, Ecol. Appl., 8, 1084–1091, 10.2307/2640963, 1998.

Fang, J., and Wang, Z.: Forest biomass estimation at regional and global levels, with special reference to China’s forest biomass, Ecol. Res., 16, 587–592, 10.1046/j.1440-1703.2001.00419.x, 2001.

Guo, Z., Fang, J., Pan, Y., and Birdsey, R.: Inventory-based estimates of forest biomass carbon stocks in China: A comparison of three methods, For. Ecol. Manage., 259, 1225–1231, 10.1016/j.foreco.2009.09.047, 2010.

Teobaldelli, M., Somogyi, Z., Migliavacca, M., and Usoltsev, V. A.: Generalized functions of biomass expansion factors for conifers and broadleaved by stand age, growing stock and site index, For. Ecol. Manage., 257, 1004–1013, 10.1016/j.foreco.2008.11.002, 2009.

Specific comments:

Line 27: China’s and here and elsewhere (lines 43, 54......).

Response: Thank you for catching that. We modified accordingly. Please see Lines 26, 43, 53, 191, 258, 260, 283, 306.

Line 28: Ecological

Response: Yes, we did (Line 27).

Line 31: using full name abbreviation for CO2.

Response: Yes, we did (Line 30).

Lines 46–48: Please revise these sentences. There are some reports in several articles.

Response: Yes, we did (Line 45).

Lines 56–63: the advantages and disadvantages of these three common methods should be described in this paragraph, especially for BEF methods you used in this study.

Response: The advantages and disadvantages of these three common methods have been described in this paragraph, please see Lines 55, 57–66.

Lines 142: add a space between 30 and years.

Response: Yes, we did (Line 167).

Lines 207: Table 1 shows a negative vale of C sink of , also Table 2 for nature forests, could you explain these results and give more detailed discussion.

Response: The forests of China, as a whole, were C sources (-2.9 Tg C/a) in 1994–1998. This is the result of forest area loss and most importantly damages of the natural forests at that period (Guo et al., 2013). The area of natural forest decreased from 1994 to 1998 (Table 2), which led to a slight decrease in the total biomass C pool. We have added discussion on this issue (Lines 222–226).

Reference: Guo, Z., Hu, H., Li, P., Li, N. and Fang, J.: Spatio-temporal changes in biomass carbon sinks in China’s forests during 1977-2008, Sci. China-Life Sci., 43, 421–431, 2013.

Lines 228-236: A constant C conversion factor of 0.5 was used to convert biomass into C in this study may be an uncertainty, different C contents for tree species and components were reported by many studies.

Response: The C conversion factor is a key parameter to the estimation. It may vary greatly among tree types, ages and organs which have been reported in many studies. With 576 observations of tree ages, size (diameter at breast height and biomass) and C concentration, a global analysis has found that the constant C concentration factor, which represents the C concentration of stem, to all trees introduced a systematic error of -2.5%–5.9% for forest C pool calculation (Ma et al., 2020). In the revision, we added the study of Ma et al. (2020) to support the application of the constant C conversion (Lines 293–294).

Reference: Ma, S., Eziz, A., Tian, D., Yan, Z., Cai, Q., Jiang, M., Ji, C. and Fang, J.: Size- and age-dependent increases in tree stem carbon concentration: implications for forest carbon stock estimations, J. Plant Ecol., 13, 233-240, 2020.

RC3

This an important contribution to the series of studies about biomass C of China’s forests.  Using standard methodology developed in previous published works, the authors have compiled a credible time series of estimated net C uptake for natural and planted forests that can help inform China’s GHG policies as well as help the world understand how massive reforestation as well as deforestation of older forests in China are influencing the global C budget.  Although not particularly innovative in methodology, the study is comprehensive and informative, and I recommend publishing after some relatively minor revisions. Most recommended revisions are for clarity of language, though two comments about the analysis are more substantive. First, there have been several papers written that challenge the success of large-scale plantings especially in areas of China subject to drought.  Do the results here conclude that most plantings have been successful as measured by the forest inventory over time?  Second, the large reduction in area and C density of natural forests in the 1994-1998 time period is quite significant, and I would like to hear more about this in the discussion.  The authors provide a few insights in lines 196-202, particularly related to aging forests and slower growth, but the references tend to be from other regions and so I would like to see some exploration of literature that nis more relevant to China. In addition, the idea that harvesting old forests and converting them to younger managed forests will result in higher growth rates is very misleading as a “natural climate solution” in that the loss of accumulated carbon in the harvested forest will not be replaced by accumulated growth of young forests for decades or centuries.

Response: Thanks for the important and helpful comments.

Firstly, we agreed that several papers pose a huge challenge to large-scale planting of plantations in arid regions of China, because several studies have found that plantations are more sensitive to drought than natural forests (Zhong et al., 2021). The main methods of afforestation in China are artificial afforestation (regeneration), aerial seeding afforestation, and mountain closure for afforestation (Wang, 2019). In China, subtly selected afforestation methods are applied according to the local environmental conditions to improve the success of afforestation. In the inventory, only those successfully established trees are taken as afforestation stands. The inventory is not a direct measure of whether a specific afforestation practice is successful or not. Changes in inventory over time reflect the overall changes of forest where areal increases are attributed to afforestation.

The forests of China, as a whole, were C sources (-2.9 Tg C/a) in 1994–1998. This is the result of forest area loss and most importantly damages of the natural forests at that period (Guo et al., 2013). The area of natural forest decreased from 1994 to 1998 (Table 2), which led to a slight decrease in the total biomass C pool. We have added discussion on this issue (Lines 222–226).

We added discussion of related studies (Guo et al., 2013; Zhao et al., 2019, 2021; Yue et al., 2018; Luyssaert et al., 2008; Zhou et al., 2006) on old-age forest biomass C pools in China, and discussion of soil C accumulation of old-age forest (Lines 233–234, 237–250). Conversion of old forests by young forests means on-site loss of forest carbon, though growing of young forest can compensate the “loss” of old forest after years. But the replaced old forest is not inevitably converted into carbon emission by full percent. Usually, the harvested timbers are turn into deposited carbon by many means such like furniture, house building and instruments etc. and only debris of harvested trees turn into dead litters. To avoid confusion, we have revised the sentence (Lines 248–250).

Reference:

Guo, Z., Hu, H., Li, P., Li, N. and Fang, J.: Spatio-temporal changes in biomass carbon sinks in China’s forests during 1977-2008, Sci. China-Life Sci., 43, 421–431, 2013.

Luyssaert, S., Schulze, E. D., Borner, A., Knohl, A., Hessenmoller, D., Law, B. E., Ciais, P., and Grace, J.: Old-growth forests as global carbon sinks, Nature, 455, 213–215, 10.1038/nature07276, 2008.

Wang, Y.: Review on China’s plantation development since the reform and opening up, Forest Resources Management, 1, 6–11, 2019.

Yue, J., Guan, J., Yan, M., Zhang, J., Deng, L., Li, G., and Du, S.: Biomass carbon density in natural oak forests with different climate conditions and stand ages in northwest China, J. For. Res., 23, 354–362, 10.1080/13416979.2018.1536313, 2018.

Zhao, M, Yang, J., Zhao, N., Liu, Y., Wang, Y., Wilson, J. and Yue, T.: Estimation of China’s forest stand biomass carbon sequestration based on the continuous biomass expansion factor model and seven forest inventories from 1977 to 2013, For. Ecol. Manage., 448, 528–534, 2019.

Zhao, M., Yang, J., Zhao, N., Liu, Y., Wang, Y., Wilson, J. P. and Yue, T.: Estimation of the relative contributions of forest areal expansion and growth to China’s forest stand biomass carbon sequestration from 1977 to 2018, J. Environ. Manage., 300, 113757, 2021.

Zhou, G., Liu, S., Li, Z., Zhang, D., Tang, X., Zhou, C., Yan, J. and Mo, J.: Old-growth forest can accumulate carbon in soils, Science, 314, 1417–1417, 2006.

Zhong, Z., He, B., Chen, Y., Yuan, W., Huang, L., Guo, L., Zhang, Y. and Xie, X.: Higher Sensitivity of Planted Forests' Productivity Than Natural Forests to Droughts in China, J. Geophys. Res.-Biogeosci., 126, 2021, https://doi.org/10.1029/2021JG006306.

Here are some specific comments for consideration:

Lines 46-48: is there a difference between “forest census data” and “survey data”?

Response: There is no difference between “forest census data” and “survey data”. To avoid ambiguity, we have replaced the word of “census” with “survey” (Line 46).

Line 51: replace “sequestrating” with “sequestering”.

Response: Thanks for your suggestion. We have modified accordingly (Line 50).

Line 52: replace “have” with “has”.

Response: Yes, we did (Line 51).

Line 54: add “net” between the words “reducing greenhouse”.

Response: Yes, we did (Line 53).

Line 102: replace “increase” with “increasing”.

Response: Yes, we did (Line 120).

Line 106: replace “may lead” with “has led”.

Response: Yes, we did (Line 124).

Line 112: replace “average” with “average increase”.

Response: Yes, we did (Line 131).

Line 127: delete “during”

Response: Yes, we did (Line 151).

Lines 148-149: please provide a clear definition of the 5 terms that describe age of forest.  Explain how these terms are associated with stages of forest succession and that the associated forest ages are different among different forest types.

Response: Good suggestion, we have added explanation and Table A6for classification of forest ages for different forest types in China (Lines 497-518).

Figure 2 uses 3 age classes that are different than the 5 classes described in lines 148-149.  Are the 3 classes aggregated from the 5 classes, or defined differently?

Response: The 3 classes are aggregated from the 5 classes. In China's forest inventory of early years, the age groups were divided into three groups, namely young forest, middle-age forest and mature forest. After 1984, the forest inventory data were divided into five age groups, namely young forest, middle-age forest, pre-mature forest, mature forest and over-mature forest. In order to implement the temporal comparison of the inventories, we aggregated the pre-mature forest, mature forest and over-mature forest into one age group—old forest. The young and middle-age forests remained unchanged. We have modified the description accordingly. Please see Lines 172, 174-176.

Line 163: Forest inventories based on sample plots are not really “spatial” in that they are based on sample points spaced some distance apart. It is more a “statistical” approach to data rather than “spatial”.

Response: Thanks for your suggestion. We have modified accordingly (Line 189).

Line 188: this would be a good place to add some further explanation for the reduction of area and stock in 1994-1998.

Response: Yes, we did (Lines 202–207).

Line 211: replace “promoting” with “the increase of”.

Response: Yes, we did (Line 260).

Lines 228-231: The errors seem rather small – what is included in the estimation of error?  Are both sampling and modeling errors estimated?  How the errors were calculated should be referenced in the methods, perhaps in the “statistical analysis” section.

Response: Phillips et al. (2000) analyzed the growing stock and its estimation error in the five southeastern of the United States, and divided the estimation error into three parts: sampling error, measurement error and regression error. The results showed that the estimation errors of regional forest accumulation and its changes were mainly caused by sampling errors (accounting for 90%–99% of the total variation) (Phillips et al., 2000). In the discussion of Lines 286–289, the error we mentioned is only sampling error. According to the forest inventory report, survey accuracy of the forest area and timber volume was over 90% (National Forestry and Grasslands Administration, 2019). Refer to the methods of Phillips et al. (2000) and Piao et al. (2009), we calculate national sampling error for growing stock change between preceding and current inventory periods, using China’s forest inventory statistics which provide area, growing stock per unit area (density of growing stock), and number of sampling plots for each forest type for each province. The measurement error was assumed to be 0 in this study because we cannot re-run the forest inventory. In the discussion of Lines 291–293, the error we mentioned was regression error. This error generated by the continuous BEF method calculated earlier by Fang and Chen (2001) of this research team when converting the growing stock to biomass at the national scale, that is, the regression error (modeling error).

According to your suggestion, we have added the calculation of sampling error in the “statistical analysis” section (Lines 104–113). Thanks again for your suggestion!

Reference:

Fang, J. and Chen, A.: Dynamic forest biomass carbon pools in China and their significance, Acta Bot. Sin., 43, 967–973, 2001.

Phillips, D. L., Brown, S., Schroeder, P. E. and Birdsey, R. A.: Towards error analysis of large-scale forest carbon budgets, Glob. Ecol. Biogeogr., 9, 305-313, 2000.

Piao, S., Fang, J., Ciais, P., Peylin, P., Huang, Y., Sitch, S. and Wang, T.: The carbon balance of terrestrial ecosystems in China, Nature, 458, 1009–U82, 2009.