Journal of Resources and Ecology >
Preliminary Estimation of Soil Carbon Sequestration of China’s Forests during 1999-2008
WANG Bin, E-mail: ylwangbin@sina.com |
Received date: 2021-07-28
Accepted date: 2021-10-16
Online published: 2022-01-08
Supported by
The Fundamental Research Funds of Chinese Academy of Forestry(CAFYBB2020SY015)
The National Forest Inventory (NFI) is an important resource for estimating the national carbon balance (These data were unpublished data, and we could only obtain the data before 2008 through data search by now). Based on the data from sample plots, the literature, and NFI, as well as the relationships between volume, biomass, annual litterfall and soil respiration of different forest types, the net ecosystem production (NEP), changes in forest biomass carbon storage (△Cbiomass) and non-respiratory losses (NR) of China’s forests during 1999-2008 were estimated, and the forest soil carbon sequestration (△Csoil) was assessed according to the carbon balance principle of the forest ecosystem (△Csoil = NEP - NR - △Cbiomass). The results showed that the total NEP, △Cbiomass, NR and △Csoil values for China’s forests were 157.530, 48.704, 31.033 and 77.793 Tg C yr-1 respectively, and average NEP, △Cbiomass, NR, and △Csoil values were 101.247, 31.303, 19.945 and 49.999 g C m-2 yr-1 respectively. There were large spatial differences in forest soil carbon sequestration in different parts of China. The forest soil in Jiangxi, Hunan, Zhejiang, Fujian, Anhui, Shanxi, Shaanxi, Guangxi and Liaoning served as carbon sources and the carbon released was about 25.507 Tg C yr-1. The other 22 provinces served as carbon sinks and the average carbon sequestration by forest soil came to 103.300 Tg C yr-1. This research established a method for evaluating soil carbon sequestration by China’s forests based on the NFI, which is a useful supplement to current statistical data-based studies on the forest ecosystem carbon cycle, and can promote comparable studies on forest soil carbon sequestration with consistent research methods at the regional scale.
WANG Bin , LIU Moucheng , ZHOU Zhichun . Preliminary Estimation of Soil Carbon Sequestration of China’s Forests during 1999-2008[J]. Journal of Resources and Ecology, 2022 , 13(1) : 17 -26 . DOI: 10.5814/j.issn.1674-764x.2022.01.002
Fig. 1 Technical route for the estimation of soil carbon sequestration by China’s forests |
Table 1 Relationships between volume, biomass, annual biomass increment (ABI) and annual litterfall. |
Forest types | N | Biomass | rBiomass | ABI | rABI | n | Annual litterfall | rAL |
---|---|---|---|---|---|---|---|---|
Cupressus funebris, Keteleeria fortunei | 10 | B=V/(1.0202+0.0022V) | 0.9605a | P=B/(0.1132A+0.0745B) | 0.9018a | 10 | L=B/(9.8381+0.1337B) | 0.7508b |
Larix | 39 | B=V/(1.1111+0.0016V) | 0.9571a | P=B/(0.1885A +0.0728B) | 0.7980a | 39 | L=B/(16.734+0.0577B) | 0.9267a |
Pinus armandii, Pinus densata and other mountain pines | 43 | B=V/(1.2390+0.0013V) | 0.9546a | P=B/(0.3840A +0.0104B) | 0.9475a | 43 | L=B/(7.5272+0.1102B) | 0.7469a |
Pinus massoniana | 46 | B=V/(1.4254+0.0004V) | 0.9587a | P=B/(0.4046A +0.0098B) | 0.9674a | 46 | L=B/(15.451+0.0225B) | 0.9319a |
Pinus yunnanensis, Pinus khasya | 41 | B=V/(1.3624-0.0003V) | 0.9951a | P=B/(0.2423A +0.0581B) | 0.9475a | 41 | L=B/(18.905+0.0422B) | 0.9847a |
Pinus tabulaeformis, Platycladus orientalis | 147 | B=V/(1.0529+0.0020V) | 0.9679a | P=B/(0.3520A+0.0161B) | 0.9760a | 147 | L=B/(11.177+0.1501B) | 0.8689a |
Pinus sylvestris var. mongolica | 7 | B=V/(1.2544+0.0030V) | 0.9129b | P=B/(0.1405A+0.1203B) | 0.9740a | 7 | L=4.20±0.3538 | |
Cunninghamia lanceolata | 70 | B=V/(1.2917+0.0022V) | 0.9541a | P=B/(0.4598A+0.0069B) | 0.9691a | 48 | L=B/(10.132+0.0874B) | 0.7783a |
22 | L=B/(8.7239+0.0418B)d | 0.9618a | ||||||
Picea, Abies, Tsuga | 154 | B=V/(1.3667+0.0012V) | 0.9228a | P=B/(0.2267A+0.0526B) | 0.8482a | 35 | L=B/(27.204+0.0812B) | 0.9580a |
119 | L=3.34±0.9277 e | |||||||
Temperate mixed coniferous-broadleaf forest | 13 | B=V/(1.1731+0.0018V) | 0.9686a | P=B/(0.1038A+0.0761B) | 0.9087a | 13 | L=3.46±0.9597 | |
Temperate typical deciduous broadleaf forest | 59 | B=V/(0.6539+0.0038V) | 0.9335a | P=B/(0.2393A+0.0495B) | 0.9565a | 59 | L=B/(18.246+0.0366B) | 0.8627a |
Subtropical evergreen broadleaf forest | 222 | B=V/(0.7883+0.0026V) | 0.8567a | P=B/(0.2503A+0.0226B) | 0.8885a | 222 | L=B/(20.507+0.0383B) | 0.9104a |
Subtropical mixed evergreen-deciduous broadleaf forest | 13 | B=V/(0.5788+0.0020V) | 0.9201a | P=B/(0.3018A+0.0331B) | 0.8219a | 13 | L=B/(9.1028+0.0575B) | 0.8746a |
Sclerophyllous evergreen Quercus forest | 8 | B=V/(0.7823+0.0014V) | 0.9111b | P=B/(0.2989A+0.0117B) | 0.9469a | 8 | L=B/(34.845+0.0283B) | 0.9003b |
Betula and Populus | 119 | B=V/(0.8115+0.0019V) | 0.9501a | P=B/(0.3080A+0.0138B) | 0.9429a | 119 | L=B/(16.722+0.0324B) | 0.9236a |
Tropical rain forest and monsoon forest | 8 | B=V/(0.6809+0.0006V) | 0.9972a | P=B/(0.1797A+0.0344B) | 0.6499c | 8 | L=B/(8.0976+0.0540B) | 0.8118b |
Note: A=Stand age; B=Stand biomass; V=Stand volume; P=Annual biomass increment; L=Annual litterfall. a means P<0.001; b means P<0.05; c means P<0.1; d only used in Guizhou Province; e only used in southwest China (Wang et al., 2010). N=Samples of each forest types for Biomass and ABI; n=Samples of each forest types for annual litterfall; rBiomass=Correlation coefficient of volume and biomass; rABI=Correlation coefficient of annual biomass increment (P) and biomass; rAL=Correlation coefficient of annual litterfall and biomass. |
Table 2 Biomass increments and non-respiratory carbon losses of different provinces or regions in China |
Province | Area (106 ha) | Carbon density (106 g C ha-1 yr-1) | Biomass/ volume (106 g m-3) | Harvest volume (106 m3 yr-1) | Emission by firea (106 g C ha-1) | Fire area (103 ha yr-1) | Total (1012 g C yr-1) | |||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
6th NFI | 7th NFI | 6th NFI | 7th NFI | Change | △Cbiomass | Harvest | Fire | |||||
Anhui | 2.455 | 2.708 | 18.245 | 21.918 | 0.735 | 0.863 | 3.640 | 3.190 | 0.649 | 1.990 | 1.571 | 0.002 |
Beijing | 0.234 | 0.356 | 19.378 | 16.313 | -0.613 | 1.117 | 0.053 | 5.650 | 0.022 | -0.218 | 0.030 | 0.000 |
Chongqing | 1.532 | 1.820 | 21.959 | 23.220 | 0.252 | 0.746 | 0.102 | 13.420 | 0.242 | 0.459 | 0.038 | 0.003 |
Fujian | 5.639 | 5.661 | 30.470 | 36.314 | 1.169 | 0.849 | 6.661 | 5.140 | 5.684 | 6.617 | 2.827 | 0.029 |
Gansu | 1.921 | 2.134 | 39.801 | 40.250 | 0.090 | 0.887 | 0.047 | 13.550 | 0.004 | 0.192 | 0.021 | 0.000 |
Guangdong | 6.606 | 6.788 | 19.529 | 20.017 | 0.097 | 0.900 | 4.108 | 2.350 | 1.584 | 0.662 | 1.849 | 0.004 |
Guangxi | 7.475 | 8.067 | 20.893 | 26.843 | 1.190 | 0.924 | 7.072 | 3.290 | 2.501 | 9.599 | 3.267 | 0.008 |
Guizhou | 3.443 | 3.981 | 21.609 | 24.949 | 0.668 | 0.827 | 1.070 | 7.680 | 2.431 | 2.659 | 0.443 | 0.019 |
Hainan | 0.892 | 0.842 | 46.218 | 49.002 | 0.557 | 1.134 | 0.754 | 11.410 | 0.228 | 0.469 | 0.428 | 0.003 |
Hebei | 2.065 | 2.882 | 16.671 | 16.247 | -0.085 | 1.118 | 0.523 | 6.900 | 0.178 | -0.244 | 0.292 | 0.001 |
Henan | 1.977 | 2.834 | 24.415 | 25.555 | 0.228 | 1.120 | 1.123 | 6.330 | 0.553 | 0.646 | 0.628 | 0.003 |
Heilongjiang | 17.922 | 19.126 | 37.906 | 40.818 | 0.582 | 1.027 | 7.057 | 13.930 | 84.107 | 11.138 | 3.622 | 1.172 |
Hubei | 4.160 | 5.078 | 17.083 | 18.526 | 0.288 | 0.898 | 1.783 | 2.540 | 1.399 | 1.465 | 0.801 | 0.004 |
Hunan | 6.091 | 7.265 | 17.208 | 19.157 | 0.390 | 0.797 | 6.242 | 2.790 | 11.912 | 2.833 | 2.489 | 0.033 |
Jilin | 7.116 | 7.267 | 53.761 | 55.640 | 0.376 | 0.958 | 4.213 | 18.580 | 0.110 | 2.732 | 2.018 | 0.002 |
Jiangsu | 0.444 | 0.744 | 25.416 | 23.909 | -0.301 | 1.017 | 0.764 | 2.490 | 0.118 | -0.224 | 0.388 | 0.000 |
Jiangxi | 7.278 | 7.681 | 17.864 | 23.331 | 1.094 | 0.907 | 5.094 | 2.890 | 5.480 | 8.400 | 2.310 | 0.016 |
Liaoning | 3.226 | 3.613 | 28.322 | 30.026 | 0.341 | 1.073 | 1.782 | 8.030 | 0.201 | 1.232 | 0.956 | 0.002 |
Inner Mongolia | 16.082 | 16.813 | 32.173 | 32.734 | 0.112 | 0.935 | 4.103 | 11.060 | 14.765 | 1.884 | 1.918 | 0.163 |
Ningxia | 0.092 | 0.111 | 21.664 | 22.831 | 0.233 | 1.029 | 0.002 | 10.260 | 0.002 | 0.026 | 0.001 | 0.000 |
Qinghai | 0.342 | 0.355 | 40.628 | 42.473 | 0.369 | 0.770 | 0.019 | 16.550 | 0.073 | 0.131 | 0.007 | 0.001 |
Shandong | 0.830 | 1.561 | 20.544 | 22.208 | 0.333 | 1.094 | 1.179 | 2.780 | 0.090 | 0.520 | 0.645 | 0.000 |
Shanxi | 1.605 | 1.724 | 19.415 | 23.690 | 0.855 | 1.069 | 0.072 | 7.740 | 0.898 | 1.474 | 0.039 | 0.007 |
Shaanxi | 5.086 | 5.670 | 30.513 | 30.607 | 0.019 | 1.026 | 0.293 | 11.080 | 0.132 | 0.107 | 0.150 | 0.001 |
Shanghai | 0.006 | 0.034 | 22.009 | 12.193 | -1.963 | 0.821 | 0.003 | 0.000 | 0.000 | -0.067 | 0.001 | 0.000 |
Sichuan | 11.036 | 11.653 | 47.540 | 46.563 | -0.195 | 0.680 | 1.248 | 13.420 | 0.752 | -2.276 | 0.424 | 0.010 |
Tianjing | 0.046 | 0.055 | 17.579 | 20.040 | 0.492 | 1.100 | 0.019 | 4.150 | 0.008 | 0.027 | 0.011 | 0.000 |
Tibet | 8.445 | 8.411 | 93.150 | 90.451 | -0.540 | 0.678 | 0.205 | 17.300 | 0.062 | -4.541 | 0.069 | 0.001 |
Xinjiang | 1.562 | 1.692 | 61.874 | 61.526 | -0.070 | 0.692 | 0.408 | 16.010 | 0.089 | -0.118 | 0.141 | 0.001 |
Yunnan | 13.566 | 14.727 | 42.958 | 41.827 | -0.226 | 0.793 | 3.208 | 14.820 | 1.841 | -3.332 | 1.272 | 0.027 |
Zhejiang | 3.615 | 3.936 | 12.387 | 18.060 | 1.135 | 0.825 | 2.062 | 2.330 | 5.092 | 4.466 | 0.851 | 0.012 |
Total/Average | 142.787 | 155.59 | 35.425 | 36.301 | 0.175 | 0.845 | 64.909 | 8.312 | 141.204 | 48.704 | 29.507 | 1.526 |
Note: NFI=National forest inventory; △Cbiomass=Change in forest biomass carbon storage. a Carbon emissions per forest area from fires by each province (Wang et al., 2001). The data in the Table exclude Taiwan, Hong Kong and Macau of China. |
Table 3 Net ecosystem production and soil carbon sequestration of different provinces or regions in China |
Province | Area (106 ha) | Total (1012 g C yr-1) | Average (g C m-2 yr-1) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
7th NFI | NPP | Rh | NEP | NR | NBP | △Cbiomas | △Csoil | NEP | NR | NBP | △Csoil | |
Anhui | 2.708 | 10.256 | 8.806 | 1.450 | 1.573 | -0.123 | 1.990 | -2.113 | 53.533 | 58.071 | -4.538 | -78.005 |
Beijing | 0.356 | 0.966 | 0.878 | 0.088 | 0.030 | 0.058 | -0.218 | 0.276 | 24.680 | 8.407 | 16.273 | 77.573 |
Chongqing | 1.820 | 6.572 | 5.905 | 0.667 | 0.041 | 0.626 | 0.459 | 0.167 | 36.628 | 2.260 | 34.368 | 9.156 |
Fujian | 5.661 | 29.020 | 22.789 | 6.232 | 2.856 | 3.376 | 6.617 | -3.241 | 110.090 | 50.456 | 59.634 | -57.262 |
Gansu | 2.134 | 9.330 | 8.072 | 1.259 | 0.021 | 1.237 | 0.192 | 1.046 | 58.968 | 0.990 | 57.978 | 48.993 |
Guangdong | 6.788 | 36.642 | 21.679 | 14.963 | 1.853 | 13.111 | 0.662 | 12.449 | 220.447 | 27.298 | 193.149 | 183.402 |
Guangxi | 8.067 | 41.723 | 29.478 | 12.244 | 3.275 | 8.970 | 9.599 | -0.629 | 151.791 | 40.598 | 111.193 | -7.803 |
Guizhou | 3.981 | 17.276 | 13.728 | 3.548 | 0.461 | 3.087 | 2.659 | 0.428 | 89.138 | 11.587 | 77.552 | 10.758 |
Hainan | 0.842 | 6.694 | 4.166 | 2.528 | 0.430 | 2.098 | 0.469 | 1.629 | 300.362 | 51.121 | 249.241 | 193.559 |
Hebei | 2.882 | 7.979 | 7.193 | 0.787 | 0.294 | 0.493 | -0.244 | 0.737 | 27.292 | 10.189 | 17.103 | 25.582 |
Henan | 2.834 | 13.099 | 9.175 | 3.924 | 0.632 | 3.292 | 0.646 | 2.646 | 138.482 | 22.299 | 116.182 | 93.391 |
Heilongjiang | 19.126 | 101.792 | 80.709 | 21.083 | 4.794 | 16.290 | 11.138 | 5.151 | 110.233 | 25.064 | 85.169 | 26.934 |
Hubei | 5.078 | 21.931 | 15.700 | 6.230 | 0.804 | 5.426 | 1.465 | 3.962 | 122.699 | 15.838 | 106.861 | 78.017 |
Hunan | 7.265 | 22.875 | 22.680 | 0.196 | 2.522 | -2.326 | 2.833 | -5.159 | 2.693 | 34.713 | -32.020 | -71.009 |
Jilin | 7.267 | 44.561 | 35.295 | 9.266 | 2.020 | 7.246 | 2.732 | 4.514 | 127.504 | 27.800 | 99.704 | 62.117 |
Jiangsu | 0.744 | 3.817 | 2.376 | 1.441 | 0.389 | 1.052 | -0.224 | 1.277 | 193.567 | 52.220 | 141.346 | 171.493 |
Jiangxi | 7.681 | 28.871 | 25.800 | 3.071 | 2.325 | 0.746 | 8.400 | -7.654 | 39.983 | 30.273 | 9.710 | -99.642 |
Liaoning | 3.613 | 14.450 | 12.568 | 1.882 | 0.958 | 0.924 | 1.232 | -0.307 | 52.074 | 26.501 | 25.573 | -8.510 |
Inner Mongolia | 16.813 | 69.169 | 59.223 | 9.946 | 2.081 | 7.864 | 1.884 | 5.981 | 59.157 | 12.380 | 46.777 | 35.573 |
Ningxia | 0.111 | 0.430 | 0.322 | 0.108 | 0.001 | 0.107 | 0.026 | 0.081 | 97.600 | 0.965 | 96.635 | 73.286 |
Qinghai | 0.355 | 1.645 | 1.321 | 0.324 | 0.009 | 0.315 | 0.131 | 0.184 | 91.209 | 2.430 | 88.779 | 51.881 |
Shandong | 1.561 | 8.380 | 4.736 | 3.644 | 0.645 | 2.998 | 0.520 | 2.479 | 233.383 | 41.340 | 192.043 | 158.760 |
Shanxi | 1.724 | 5.293 | 5.168 | 0.126 | 0.046 | 0.080 | 1.474 | -1.394 | 7.283 | 2.648 | 4.634 | -80.870 |
Shaanxi | 5.670 | 18.534 | 18.994 | -0.460 | 0.152 | -0.612 | 0.107 | -0.719 | -8.113 | 2.677 | -10.790 | -12.672 |
Shanghai | 0.034 | 0.097 | 0.084 | 0.013 | 0.001 | 0.012 | -0.067 | 0.079 | 39.426 | 3.044 | 36.382 | 232.689 |
Sichuan | 11.653 | 53.595 | 44.134 | 9.461 | 0.434 | 9.027 | -2.276 | 11.303 | 81.193 | 3.728 | 77.465 | 96.999 |
Tianjing | 0.055 | 0.256 | 0.152 | 0.104 | 0.011 | 0.094 | 0.027 | 0.067 | 191.215 | 19.566 | 171.650 | 122.423 |
Tibet | 8.411 | 56.276 | 43.329 | 12.947 | 0.070 | 12.877 | -4.541 | 17.417 | 153.925 | 0.837 | 153.088 | 207.069 |
Xinjiang | 1.692 | 8.739 | 7.117 | 1.622 | 0.143 | 1.480 | -0.118 | 1.597 | 95.851 | 8.429 | 87.422 | 94.380 |
Yunnan | 14.727 | 85.799 | 58.003 | 27.796 | 1.299 | 26.497 | -3.332 | 29.829 | 188.741 | 8.820 | 179.921 | 202.547 |
Zhejiang | 3.936 | 13.144 | 12.104 | 1.039 | 0.863 | 0.177 | 4.466 | -4.290 | 26.408 | 21.924 | 4.484 | -108.988 |
Total/Average | 155.590 | 739.213 | 581.683 | 157.530 | 31.033 | 126.497 | 48.704 | 77.793 | 101.247 | 19.945 | 81.301 | 49.999 |
Note: NFI=National forest inventory; NPP=Net primary production; Rh=Heterotrophic respiration; NEP=Net ecosystem production; NR=Non-respiratory carbon losses; NBP=Net biome production; △Cbiomass=Changes in forest biomass carbon storage; △Csoil=Forest soil carbon sequestration. The data here exclude Taiwan, Hong Kong and Macau of China. |
We thank the Chinese Ecosystem Research Network for providing the research data.
[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] |
State Administration of Forestry of China. 2006. Chinese forestry statistical yearbook (1999-2003). Beijing, China: China Forestry Publishing House. (in Chinese)
|
[32] |
State Administration of Forestry of China. 2010. Chinese forestry statistical yearbook (2004-2008). Beijing, China: China Forestry Publishing House. (in Chinese)
|
[33] |
|
[34] |
|
[35] |
|
[36] |
|
[37] |
|
[38] |
|
[39] |
|
[40] |
|
[41] |
|
[42] |
|
[43] |
|
[44] |
|
[45] |
|
[46] |
|
[47] |
|
[48] |
|
[49] |
|
/
〈 |
|
〉 |