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Biomass carbon stocks in China's forest between 2000 and 2050


SCIENCE CHINA
Life Sciences
? REVIEW AND META-ANALYSIS ?
July 2010 Vol.53 No.7: 776–783 doi: 10.1007/s11427-010-4030-4

Biomass carbon stocks in China’s forests between 2000 and 2050: A prediction based on forest biomass–age relationships
XU Bing, GUO ZhaoDi, PIAO ShiLong & FANG JingYun*
Department of Ecology, College of Urban and Environmental Sciences, and Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing 100871, China Received February 22, 2010; accepted June 21, 2010

China’s forests are characterized by young forest age, low carbon density and a large area of planted forests, and thus have high potential to act as carbon sinks in the future. Using China’s national forest inventory data during 1994–1998 and 1999–2003, and direct field measurements, we investigated the relationships between forest biomass density and forest age for 36 major forest types. Statistical approaches and the predicted future forest area from the national forestry development plan were applied to estimate the potential of forest biomass carbon storage in China during 2000–2050. Under an assumption of continuous natural forest growth, China’s existing forest biomass carbon (C) stock would increase from 5.86 Pg C (1 Pg=1015 g) in 1999–2003 to 10.23 Pg C in 2050, resulting in a total increase of 4.37 Pg C. Newly planted forests through afforestation and reforestation will sequestrate an additional 2.86 Pg C in biomass. Overall, China’s forests will potentially act as a carbon sink for 7.23 Pg C during the period 2000–2050, with an average carbon sink of 0.14 Pg C yr?1. This suggests that China’s forests will be a significant carbon sink in the next 50 years. forest biomass–age relationship, carbon pool, carbon sink, forest inventory data, forest volume
Citation: Xu B, Guo Z D, Piao S L, et al. Biomass carbon stocks in China’s forests between 2000 and 2050: A prediction based on forest biomass–age relationships. Sci China Life Sci, 2010, 53: 776–783, doi: 10.1007/s11427-010-4030-4

Forest ecosystems contain 50%–60% of the carbon stored in terrestrial ecosystems and play an important role in alleviating atmospheric CO2 elevation and stabilizing global climate [1]. After five decades of development since 1949, China’s forests have the following characteristics: (i) young forest age—more than one-third of the total forest area is covered by young forests [2]; (ii) low average carbon density—the average carbon density of China’s forests is 41.1 Mg C ha?1 at present, and 78.7% of forests have a carbon density lower than 50 Mg C ha?1 [3]; and (iii) large area of planted forests—plantation area (32.3×106 ha) accounts for 23% of the total forest area and is continually increasing [3–6]. These characteristics imply that China’s forests have high potential to act as carbon sinks in the future.
*Corresponding author (email: jyfang@urban.pku.edu.cn) ? Science China Press and Springer-Verlag Berlin Heidelberg 2010

China has the largest area of planted forests in the world [7]. Over the last three decades, the Chinese government has conducted a number of key forestry projects, such as the Grain-for-Green Project, the Three North Shelterbelt Project, the Yangzi River Basin Shelterbelt Project and the BeijingTianjin Sandstorm Source Control Project. Most of these planted forests are still young and have a large capacity for carbon sequestration [8–11]. Since the mid-1990s, several studies have estimated China’s forest biomass carbon storage and its changes [3,12–14]. It has been suggested that the biomass carbon pool of China’s forests has increased by 1.55 Pg C, with an average rate of increase of 0.075 Pg C yr?1 over the past 22 years [3,14]. However, our knowledge of future forest biomass C stock change is limited and an accurate prediction of the potential of China’s forest biomass to act as a carbon sink is important for emission relife.scichina.com www.springerlink.com

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duction policy-making. The primary goal of this study was to estimate potential changes in China’s forest biomass carbon storage between 2000 and 2050. To do so, we first developed the relationships between forest biomass density and forest age for 36 major forest types at national scale based on forest area and timber volume data by age class and forest type from China’s national forest inventories. Using these biomass-age relationships and projected forest area from a national forestry development plan, we calculated China’s forest biomass carbon storage potential from 2000 to 2050.

where x is the timber volume per unit area, a and b are constants for a specific forest type, B is biomass density and BEF is the biomass expansion factor. This method was used to calculate the average biomass density for each forest type and age class. 1.3 Relationships between biomass density and forest age Based on the classification of forest age for different forest types (Appendix Table 1) [16], we used the median value of an age class to represent the average age of the age class. We used logistic curves to fit the relationship between biomass density and forest age for each forest type. The equation is given as follows:
B? w , 1 ? ke? at

1 Data and methods
1.1 Data sources This study was based on national forest inventory data and field measurement data. We used Chinese national forest inventory data from four inventory periods (1984–1988, 1989–1993, 1994–1998 and 1999–2003). According to China’s forest inventory, there are three major categories of forests: stands (including natural and planted forests), economic forests and bamboo forests. As stands are the major portion of forests in China, we did not consider economic forests and bamboo forests. Due to a lack of data, forests in Hong Kong, Macao and Taiwan were not included. In these inventories, forests (stands) included 36 forest types and were divided into five age classes: young-aged, middle-aged, premature, mature and overmature forests (this classification was used after 1984). These age classes were used for each forest type based on the dominant tree species and its developmental stage. Timber volume and forest area were reported for each forest type and age class. Since 1994, China has changed its definition of forests from >30% to >20% canopy coverage. Thus, we only used forest inventory data from 1994–1998 and 1999–2003 to establish the relationships between biomass density and forest age. Direct field measurements of forest biomass were primarily collected from published literature. For details, see Fang et al. [3,5] 1.2 Estimating biomass density

(1)

where B is biomass density, t is forest age and w, a and k are constants for a specific forest type. Non-linear regressions were completed using the statistical software SPSS version 13.0 (2001, SPSS Inc., USA). 1.4 Future biomass C stock prediction

Assuming that forest area in the national forest inventory during 1999–2003 represents the state of forest distribution in 2000 and that neither clear-cuts nor die-offs will occur in the next 50 years, we calculated China’s total biomass C stock of existing forest for a particular year using the following equation:
C?t ? ?? c ? Aij ? Bij ? ?? c ? Aij ?
i ?1 j ?1 i ?1 j ?1 36 5 36 5

wi
1 ? ki e

? ai tij ? ?t

?

?

,

(2)

We used the continuous biomass expansion factor method to estimate biomass C stock for each forest type and inventory period [3,15]. We first calculated volume density for each forest type and each age class based on total volume and total area and then estimated biomass density using the continuous biomass expansion factor. The equations are given as follows:

BEF=a ?

b , x B ? BEF ? x ,

where C?t is the total biomass C stock of China’s existing forests ?t years after 2000; i and j indicate forest type and age class, respectively; c is the conversion factor between biomass and C stock (0.5 in this study); Aij is the forest area for forest type i and age class j; Bij is the biomass density function for type i and age class j (eq. (1)); wi, ki and ai are constants of logistic curve for forest type i; tij is the present age for forest type i and age class j; and Δt is years after 2000. We also estimated China’s total biomass C stock for newly planted forests. The total area of newly planted forests was estimated based on the development goals of China’s forestry for the next 50 years provided by the China Forestry Sustainable Development Strategy Research Group [7] (Appendix Table 2). Here, we assumed that the current proportion of forest stands in total forest (87.5%) will not change in the next 50 years; therefore, the area of forest stands for the next 50 years can be calculated. Assuming that neither clear-cuts nor die-offs will occur, the area of

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newly planted forests can be calculated by the change in total forest stands area. Because the logistic curve is provided for each forest type, the area of newly planted forest should be allocated into different forest types. Assuming that the planted forest area in recent years is a reflection of future trends in forest area expansion, we allocated the newly planted forest area among forest types based on the proportion of planted forest area reported by the Forest Resource Statistics of China (1999–2003) [2]. The estimated change in newly planted forest area for all forest types is shown in Appendix Table 3. Finally, the biomass C stock of newly planted forests was also calculated using eq. (2) based on the estimated area. By summarizing the results of existing forests and newly
Table 1

planted forests, we can obtain the changes in total biomass C stock of China’s forests in the future.

2 Results
2.1 Relationships between biomass density and forest age The relationships between biomass density and forest age for all forest types are shown in Table 1. The explanation of forest age on biomass density (R2) are generally high for most forest types. Among the 36 forest types, 31 had a R2 higher than 0.8. Figure 1 illustrates the fit logistic curves for four forest types that had the largest forest areas.

Parameters of logistic curves fitting the relationships between biomass density and forest agea) Forest type Total P. koraiensis Abies Picea Tsuga Cupressus Larix P. sylvestris var. mongolica P. densiflora P. thunbergii P. tabulaeformis P. armandii Keteleeria P. massoniana P. yunnanensis P. kesiya var. langbianensis P. densata Cunninghamia Cryptomeria Metasequoia Fraxinus mandschurica, Juglans mandshurica, Phellodendron Cinnamomum Phoebe Oaks Betula Other Hard Broad-leaved Tilia Sassafras Eucalyptus Casuarina Populus Paulownia Other Soft Broad-leaved Nonmerchantable woods Mixed conifer Mixed conifer and deciduous Mixed Broad-leaved w 201.19 218.56 357.50 274.47 203.06 155.72 130.20 201.71 49.14 60.00 87.98 91.06 67.22 81.67 147.88 95.71 162.21 69.61 111.63 140.00 212.83 120.00 206.99 197.09 163.34 160.99 266.71 210.00 89.87 156.02 70.76 110.42 132.24 199.15 158.94 290.96 237.57 k 6.727 7.954 4.345 5.738 4.804 10.568 2.659 10.879 2.344 3.360 12.236 3.283 0.647 2.174 5.334 2.067 3.626 2.437 2.513 12.320 8.067 5.400 9.186 8.491 7.479 10.313 7.823 24.990 7.149 6.443 1.492 4.095 5.276 20.730 20.804 8.577 12.272 a 0.0617 0.0360 0.0211 0.0295 0.0201 0.0443 0.0696 0.1059 0.0985 0.0823 0.1144 0.0678 0.0238 0.0522 0.0736 0.0878 0.0578 0.0963 0.1113 0.2046 0.0607 0.0566 0.0615 0.0422 0.0516 0.0492 0.0586 0.1708 0.1432 0.0698 0.1434 0.0505 0.1302 0.3534 0.1017 0.0560 0.1677 R2 0.988 0.950 0.920 0.983 0.963 0.912 0.981 0.930 0.665 0.655 0.977 0.873 0.765 0.996 0.731 0.832 0.966 0.963 0.939 0.577 0.994 0.394 0.900 0.992 0.990 0.990 0.957 0.878 0.898 0.804 0.934 0.876 0.956 0.975 0.949 0.993 0.980

Number 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

a) The equation is B ?

w 1 ? ke? at

, where B is biomass density, t is forest age and w, k and a are parameters.

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2.2 Prediction of existing forest and newly planted forest biomass C stock Table 2 shows estimates of biomass C stock for existing forests during 2000–2050. Total forest biomass C stock will increase from 5.86 Pg C during 1999–2003 to 10.23 Pg C in 2050 with a net increase of 4.37 Pg C. The average biomass carbon density will increase from 41.1 Mg C ha?1 in 1999–2003 to 71.7 Mg C ha?1 in 2050. Newly planted forests will accumulate 2.86 Pg C in biomass by 2050, with an average biomass carbon density of 34.0 Mg C ha?1 (Table 2). Based on changes in biomass C stocks of both existing forests and newly planted forests, we calculated the changes in total forest biomass C stock of China’s forests in the next five decades (Figure 2 and Table 2). In 2050, the total bio-

mass C stock of China’s forests will be 13.09 Pg C, which is 7.23 Pg C higher than that in 1999–2003. This suggests that biomass of China’s forests will act as a carbon sink of 0.14 Pg C yr?1 during 2000–2050. The overall average biomass carbon density of China’s forests will increase from 41.1 Mg C/ha during 1999–2003 to 57.7 Mg C ha?1 in 2050, with a net increase of 16.6 Mg C ha?1.

3 Discussion
3.1 Methods and uncertainties in predicting forest biomass C stock Several methods have been developed to estimate forest biomass C stock at national and provincial scales [14].

Figure 1

Logistic curves between biomass density and forest age for the four major forest types (Mg=106 g).

Table 2

Prediction of China’s forest biomass C stocks in 2000–2050 (Tg=1012 g, Mg=106 g) carbon stock (Tg C) 7385.0 8536.5 9299.9 9839.3 10234.7 4372.3 87.4 Existing forest carbon density (Mg C ha?1) 5862.5 41.1 51.7 59.8 65.1 68.9 71.7 carbon stock (Tg C) 0.0 303.7 880.3 1538.5 2196.9 2855.6 2855.6 57.1 New forest carbon density (Mg C ha?1) 0.0 15.7 19.8 25.2 30.3 34.0 Total carbon stock (Tg C) 5862.5 7688.6 9416.8 10838.4 12036.2 13090.3 7227.9 144.6 carbon density (Mg C ha?1) 41.1 47.4 50.3 53.2 55.9 57.7

Year 2000 2010 2020 2030 2040 2050 Carbon sink (Tg C) Average annual carbon sink (Tg C yr?1)

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Figure 2

Prediction of China’s forest biomass C stocks during 2000–2050 (Pg=1015 g).

However, we do not see a universally accepted approach for predicting future changes in forest biomass C stock [17,18]. In this paper, we present an approach using forest inventory data and forestry development goals to predict China’s forest biomass C stock at the national scale. Because the relationship between biomass density and forest age for each forest type was derived from the data of two inventory periods (1994–1998 and 1999–2003) the data included the influence of historic human management such as thinning and replanting, and thus the prediction in this study has already involved the influence of human activities and historic factors on forest biomass C stock. Thus, the results from this prediction can reflect the actual changes in forest biomass C stock in the future. To test the reliability of this prediction, we applied the established relationship between biomass density and forest age for each forest type to estimate C stocks for the past four inventory periods (1984–1988, 1989–1993, 1994–1998 and 1999–2003) and then compared these with the estimates induced from the continuous-BEF method by Fang et al. [3] (Figure 3). Statistical analysis suggests that there is no significant difference between the estimates derived from these two approaches. The small range of differences, ?2.1% to

+3.6%, suggests that the prediction of forest biomass C stocks used in this study is reasonable at national scale. However, large uncertainties still exist in this prediction because several assumptions were used. First, we assumed that no large areas of clear-cuts or die-offs would occur and that all existing forests would grow naturally according to an average growth curve. In fact, if clear-cuts and die-offs do occur, even if the forest area still increases as projected in the forestry development goals, some mature forests with high biomass density will be replaced by young forests with low biomass density. This may result in an overestimation of carbon sinks. For instance, based on China’s sixth national forest inventory (1999–2003), the total consumption of forest stands in China is 37244.8×104 m3 yr?1, and total mortality is 7242.6×104 m3 yr?1. If mortality remains unchanged in the future, based on the present ratio between forest volume and C stock [3], China’s forests may lose 1.75 Pg C in the next 50 years, and the total carbon sink during 2000–2050 will drop from 7.23 Pg C to 5.48 Pg C. Second, uncertainty in our prediction might occur from the allocation of the newly planted forest area in each forest type. We allocated newly planted forest area into each forest type using the current ratio reported in the recent national forest inventory of 1999–2003. However, the proportion of different forest types in newly planted forests may change in the future. Third, biomass carbon accumulation in forests can also be influenced by climate change, elevation of atmospheric CO2 and N deposition [19–21], which were not taken into account in this study. Finally, whether the forestry development goals given by the China Forestry Sustainable Development Strategy Research Group [7] can be achieved will be crucial to the accuracy of our prediction. 3.2 Potential of China’s forest biomass carbon sink

Figure 3 Comparison between actual and predicted values of forest biomass C stocks for the four forest inventory periods.

Our results show that China’s forest biomass carbon storage will increase by 7.23 Pg C in 2000–2050, which is 123% of current biomass carbon pools. The carbon sink during 2000–2050 will be approximately four times the carbon sink in the past 20 years. Average biomass carbon density will exceed 50 Mg C ha?1 in 2020 and reach 57.7 Mg C ha?1 in 2050. The IPCC (2007) [22] has suggested that global forests have sequestrated 60–87 Pg C during 1995–2005, compensating for 12%–15% of the cumulated fossil carbon emission during the same period. Based on forest inventory data, China’s forest biomass C stocks have removed 14.6%– 16.1% of China’s fossil carbon emissions during 1981–2000 [3], which is comparable to the global average. This study, however, only considers forest stands. It has been suggested that the total carbon sink of China’s forests could increase by 20%–30% if economic and bamboo forests are included (Fang et al. unpublished data). Since the 1980s, China’s

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CO2 emissions have increased dramatically, and with the rapid development of the economy, emissions will continue to grow [23]. Fossil fuel combustion in China was estimated to produce emissions of 101.5–155.9 Pg C during 2005– 2050 [24]. According to our prediction, China’s forest biomass C sinks could offset 4.6%–7.1% of fossil CO2 emissions during 2000–2050, suggesting that biomass carbon sinks of China’s forests can continue to play an important role in mitigating increases in greenhouse gas emissions. Therefore, forest protection and forest management in China are of critical importance to reduce China’s CO2 emissions.

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Dixon R K, Brown S, Houghton R A, et a1. Carbon pools and flux of global forest ecosystem. Science, 1994, 262: 185–190 Chinese Ministry of Forestry. Forest Resource Statistics of China (1999–2003) (in Chinese). Department of Forest Resource and Management, Chinese Ministry of Forestry, 2005 Fang J Y, Guo Z D, Piao S L, et al. Terrestrial vegetation carbon sinks in China, 1981–2000. Sci China Ser D-Earth Sci, 2007, 50: 1341–1350 Fang J Y, Wang G G, Liu G H, et al. Forest biomass of China: An estimate based on the biomass-volume relationship. Ecol Appl, 1998, 8: 1084–1091 Fang J Y, Chen A P, Peng C H, et al. Changes in forest biomass carbon storage in China between 1949 and 1998. Science, 2001, 292: 2320–2322 Pan Y D, Luo T X, Birdsey R, et al. New estimates of carbon storage and sequestration in China’s forest: Effect of age class and Method on inventory-based carbon estimation. Clim Change, 2004, 67: 211–236 China forestry sustainable development strategy research group. General view of China forestry sustainable development strategy research (in Chinese). Beijing: China forestry publishing house, 2002 Pregitzer K S, Euskirchen E S. Carbon cycling and storage in world forests: biome patterns related to forest age. Glob Change Biol, 2004, 10: 2052–2077 Zhao M, Zhou G S. Estimation of biomass and net primary productivity of major planted forest in China based on forest inventory data. For Ecol Manag, 2005, 207: 295–313

16 17 18

19

20

21

22

23

24

Kauppi P E, Ausubel J H, Fang J Y, et al. Returning forests analyzed with the forest identity. Proc Natl Acad Sci USA, 2006, 103: 17574–17579 Wang X K, Feng Z W, Ouyang Z Y. The impact of human disturbance on vegetative carbon storage in forest ecosystems in China. For Ecol Manag, 2001, 148: 117–123 Piao S L, Fang J Y, Zhu B, et al. Forest biomass carbon stocks in China over the past 2 decades: Estimation based on integrated inventory and satellite data. J Geophy Res, 2005, 110, G01006, doi: 10.1029/2005JG000014 Piao S L, Fang J Y, Ciais P, et al. The Carbon balance of terrestrial ecosystems in China. Nature, 2009, 458: 1009–1013 Guo Z D, Fang J Y, Pan Y D, et al. Inventory-based estimates of forest biomass carbon stocks in China: A comparison of three methods. For Ecol Manag, 2009, 259: 1225–1231 Fang J Y, Oikawa T, Kato T, et al. Biomass carbon accumulation by Japan’s forests from 1947 to 1995. Glob Biogeo Cyc, 2005, 19, GB2004, doi: 10.1029/2004GB002253. Xiao X W, eds. Forest Resource Inventory of China (in Chinese). Beijing: China Forestry Publishing House, 2005 Mickler R A, Earnhardt T S, Moore J A. Regional estimation of current and future forest biomass. Environ Pollut, 2002, 116: S7–S16 Zhao M F, Xiang W H, Peng C H, et al. Simulating age-related changes in carbon storage and allocation in a Chinese fir plantation growing in southern China using the 3-PG model. For Ecol Manag, 2009, 257: 1520–1531 Hyvonen R, Agren G I, Linder S, et al. The likely impact of elevated CO2, nitrogen deposition, increased temperature and management on carbon sequestration in temperate and boreal forest ecosystems: a literature review. New Phytol, 2007, 173: 463–480 Ju, W M, Chen J M, Harvey D, et al. Future carbon balance of China’s forests under climate change and increasing CO2. J Environ Manag, 2007, 85: 538–562 Luyssaert S, Inglima I, Jung M, et al. CO2 balance of boreal, temperate, and tropical forests derived from a global database. Glob Change Biol, 2007, 13: 2509–2537 IPCC. Climate Change 2007: The physical scientific basis. The Fourth Assessment Report of Working Group. Cambridge: Cambridge University Press, 2007 Raupach M R, Marland G, Ciais P, et al. Global and regional drivers of accelerating CO2 emissions. Proc Natl Acad Sci USA, 2007, 104: 10288–93 Consulting Special Report, Chinese Academy of Sciences. The scientific basis and propose of Copenhagen climate change negotiation in 2009 (in Chinese), 2009

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Appendix Table 1

Classification of forest ages for different forest types [16] Region North Origin Natural Planted Natural Planted Natural Planted Natural Planted Natural Planted Natural Planted Planted Planted Natural Planted Natural Planted Natural Planted Planted Age group (years) young-aged <60 <40 <40 <20 <40 <20 <40 <20 <30 <20 <20 <10 <10 <5 <30 <20 <20 <10 <40 <20 <10 middle-aged 61–100 41–60 41–60 21–40 41–80 21–30 41–60 21–30 31–50 21–30 21–30 11–20 11–15 6–10 31–50 21–30 21–40 11–20 41–60 21–40 11–20 per-mature 101–120 61–80 61–80 41–60 81–100 31–40 61–80 31–40 51`60 31–40 31–40 21–30 16–20 11–15 51–60 31–40 41–50 21–30 61–80 41–50 21–25 mature 121–160 81–120 81–120 61–80 101–140 41–60 81–120 41–60 61–80 41–60 41–60 31–50 21–30 16–25 61–80 41–60 51–70 31–50 81–120 51–70 26–35 over mature 161 121 121 81 141 61 121 61 81 61 61 51 31 26 81 61 71 51 121 >71 >36 Age span 20 20 20 20 20 10 20 10 10 10 10 10 5 5 10 10 10 10 20 10 5

Forest types

P. koraiensis, Picea, Cupressus, Tsuga

North South South North North South South North North South South North South North North South South North & South North & South South

Larix, Abies, P. sylvestris var. mongolica, P. densiflora, P. thunbergii P. tabulaeformis, P. massoniana, P. yunnanensis, P. kesiya var. langbianensis, P. armandii, P. densata Populus, Eucalyptus, Sassafras, Paulownia, Casuarina, etc.

Betula, Ulmus, Schima, Liquidambar, Davidia

Oaks, Cinnamomum, Phoebe, Tilia, Fraxinus mandschurica, Juglans mandshurica, Phellodendron, etc. Cunninghamia, Cryptomeria, Metasequoia

Appendix Table 2

Future changes in forest area Coverage (%) 18.2 20.4 23.5 25.5 26.9 28.4 Total forest area (104 ha) 17490.9 19568.4 22528.9 24503.3 25865.0 27226.6 Stands area (104 ha) 14278.7 16213.0 18714.0 20382.0 21532.3 22682.6 1934.3 2501.0 1668.0 1150.3 1150.3 New forest area (104 ha)

Year 2000 2010 2020 2030 2040 2050

Coverage data cited from the General View of China Forestry Sustainable Development Strategy Research (2002) [7]. Total forest area was calculated from coverage and the total land area of China (960.27×106 ha). We subtracted the area of special shrubs and forests in Hong Kong, Macao and Taiwan from the total forest area and calculated the stands area using the area ratio of stands and total forest in the forest inventory data from 1999 to 2003.

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Appendix Table 3

Area of newly planted foresta) Forest type Area of existing forest (104 ha) 14278.67 40.28 326.71 450.07 23.46 319.79 1049.39 69.4 16.14 19.48 228.1 78.38 26.92 1739.2 477.94 56.14 180.47 1381.59 23.32 7.97 65.37 8.87 10.53 1821.77 1138.83 974.04 74.74 3.59 82.19 12.85 704.44 19.01 619.69 383.67 168.54 428.02 1247.77 Area proportion 100.00% 0.08% 0.62% 0.85% 0.04% 2.40% 7.88% 0.13% 0.03% 0.04% 1.71% 0.15% 0.05% 18.06% 0.91% 0.11% 0.34% 28.54% 0.04% 0.02% 0.12% 0.02% 0.02% 3.45% 2.16% 7.31% 0.14% 0.01% 0.62% 0.02% 12.81% 0.04% 4.65% 0.73% 0.32% 3.21% 2.37% Area of newly planted forest (104 ha) 2010 1934.33 1.48 11.98 16.50 0.86 46.44 152.41 2.54 0.59 0.71 33.13 2.87 0.99 349.40 17.53 2.06 6.62 552.01 0.86 0.29 2.40 0.33 0.39 66.80 41.76 141.47 2.74 0.13 11.94 0.47 247.78 0.70 90.00 14.07 6.18 62.16 45.75 2020 4435.34 3.39 27.47 37.84 1.97 106.50 349.47 5.84 1.36 1.64 75.96 6.59 2.26 801.16 40.19 4.72 15.17 1265.74 1.96 0.67 5.50 0.75 0.89 153.17 95.75 324.38 6.28 0.30 27.37 1.08 568.15 1.60 206.37 32.26 14.17 142.54 104.91 2030 6103.31 4.66 37.80 52.07 2.71 146.55 480.89 8.03 1.87 2.25 104.53 9.07 3.11 1102.44 55.30 6.50 20.88 1741.73 2.70 0.92 7.56 1.03 1.22 210.78 131.76 446.36 8.65 0.42 37.66 1.49 781.80 2.20 283.98 44.39 19.50 196.14 144.37 2040 7253.62 5.54 44.92 61.89 3.23 174.17 571.53 9.54 2.22 2.68 124.23 10.78 3.70 1310.22 65.72 7.72 24.82 2070.00 3.21 1.10 8.99 1.22 1.45 250.50 156.59 530.49 10.28 0.49 44.76 1.77 929.15 2.61 337.50 52.76 23.18 233.11 171.57 2050 8403.94 6.42 52.05 71.70 3.74 201.79 662.16 11.06 2.57 3.10 143.93 12.49 4.29 1518.00 76.14 8.94 28.75 2398.27 3.72 1.27 10.41 1.41 1.68 290.23 181.43 614.62 11.91 0.57 51.86 2.05 1076.50 3.03 391.02 61.12 26.85 270.08 198.78

Number 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 Total

P. koraiensis Abies Picea Tsuga Cupressus Larix P. sylvestris var. mongolica P. densiflora P. thunbergii P. tabulaeformis P. armandii Keteleeria P. massoniana P. yunnanensis P. kesiya var. langbianensis P. densata Cunninghamia Cryptomeria Metasequoia Fraxinus mandschurica, Juglans mandshurica, Phellodendron Cinnamomum Phoebe Oaks Betula Other Hard Broad-leaved Tilia Sassafras Eucalyptus Casuarina Populus Paulownia Other Soft Broad-leaved Nonmerchantable woods Mixed conifer Mixed conifer and deciduous Mixed Broad-leaved

a) The area proportion of newly planted forests was calculated based on the Forest Resource Statistics of China (1999–2003) [2]. These data gave the exact planted forest area for the top three forest types in China (Cunninghamia, P. massoniana and Populus) and the proportion of area of planted forests for the top ten forest types. Therefore, we assigned the newly planted forest area based on the present planted forest area proportions, and when the date of planted forest was unavailable, we assigned the area based on the area proportion of forest stands.


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