资源与生态学报 ›› 2022, Vol. 13 ›› Issue (1): 17-26.DOI: 10.5814/j.issn.1674-764x.2022.01.002
收稿日期:
2021-07-28
接受日期:
2021-10-16
出版日期:
2022-01-30
发布日期:
2022-01-08
通讯作者:
周志春
WANG Bin1(), LIU Moucheng2, ZHOU Zhichun1,*(
)
Received:
2021-07-28
Accepted:
2021-10-16
Online:
2022-01-30
Published:
2022-01-08
Contact:
ZHOU Zhichun
About author:
WANG Bin, E-mail: ylwangbin@sina.com
Supported by:
摘要:
基于样地资料、文献资料和森林资源清查资料,以及不同森林类型蓄积、生物量、年凋落量和土壤呼吸之间的函数关系,估算1999-2008年间中国森林生态系统的NEP(净生态系统生产力)、△Cbiomass(现存森林植被碳储量增量)和NR(非呼吸代谢消耗光合产物),再根据森林生态系统碳平衡方程,初步估算中国森林土壤碳汇(△Csoil = NEP-△Cbiomass-NR)。研究结果表明:中国森林生态系统总的NEP、△Cbiomass、NR和△Csoil分别为157.530、48.704、31.033和77.793 Tg C yr?1,单位面积NEP、△Cbiomass、NR和△Csoil分别为101.247、31.303、19.945和49.999 g C m?2 yr?1。中国森林土壤碳汇存在较大的空间差异,江西、湖南、浙江、福建、安徽、山西、陕西、广西和辽宁9省(区)森林土壤为碳源,释放的碳约为25.507 Tg C yr-1。其他22个省(区)森林土壤为碳汇,吸收的碳约为103.300 Tg C yr-1。本研究建立了基于森林资源清查资料的中国森林土壤碳汇评价方法,是对现有的基于统计资料进行森林生态系统碳循环研究的有益补充,将推动具有可比性的、按照一致性的研究方法开展的区域尺度森林土壤固碳功能研究。
王斌, 刘某承, 周志春. 1999-2008年间中国森林土壤碳汇功能初步估算[J]. 资源与生态学报, 2022, 13(1): 17-26.
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.
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 |
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 |
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 |
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 |
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 |
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 |
[1] | Baker J M, Ochsner T E, Venterea R T, et al. 2007. Tillage and soil carbon sequestration-What do we really know? Agriculture, Ecosystems & Environment, 118(1-4): 1-5. |
[2] |
Bazrgar A B, Ng Aeryn, Coleman Brent, et al. 2020. Long-term monitoring of soil carbon sequestration in woody and herbaceous bioenergy crop production systems on marginal lands in Southern Ontario, Canada. Sustainability, 12: 3901. DOI: 10.3390/su12093901.
DOI URL |
[3] |
Bond-Lamberty B, Wang C K, Gower S T. 2004. A global relationship between the heterotrophic and autotrophic components of soil respiration? Global Change Biology, 10(10): 1756-1766.
DOI URL |
[4] | Chen G S, Yang Y S, Lu P P, et al. 2008. Regional patterns of soil respiration in China’s froests. Acta Ecologica Sinica, 28(4): 1748-1761. (in Chinese) |
[5] |
Davidson E A, Savage K, Bolstad P, et al. 2002. Belowground carbon allocation in forests estimated from litterfall and IRGA-based soil respiration measurements. Agricultural and Forest Meteorology, 113(1-4): 39-51.
DOI URL |
[6] |
Dixon R K, Solomon A M, Brown S, et al. 1994. Carbon pools and flux of global forest ecosystems. Science, 263(5144): 185-190.
PMID |
[7] |
Dunne J A, Saleska S R, Fischer M L, et al. 2004. Integrating experimental and gradient methods in ecological climate change research. Ecology, 85(4): 904-916.
DOI URL |
[8] |
Fang J, Chen A, Peng C, et al. 2001. Changes in forest biomass carbon storage in China between 1949 and 1998. Science, 292(5525): 2320-2322.
PMID |
[9] | Fang J Y, Guo Z D, Piao S L, et al. 2007. Terrestrial vegetation carbon sinks in China, 1981-2000. Science in China (Series D): Earth Sciences, 50(9): 1341-1350. |
[10] | Fang J Y, Ke J H, Tang Z Y, et al. 2001. Implications and estimations of four terrestrial productivity parameters. Acta Phytoecologica Sinica, 25(4): 414-419. (in Chinese) |
[11] | Fang J Y, Liu G H, Xu S L. 1996. Biomass and net production of forest vegetation in China. Acta Ecologica Sinica, 16(5): 497-508. (in Chinese) |
[12] | Ghasemi A F. 2018. Soil carbon sequestration and understory plant under needle and broadleaved plantations (Case study: Shahed Forest Park of Malayer City). Ecopersia, 6(1): 1-10. |
[13] |
Gower S T, Pongracic S, Landsberg J J. 1996. A global trend in belowground carbon allocation: Can we use the relationship at smaller scales? Ecology, 77(6): 1750-1755.
DOI URL |
[14] |
Hart S C, Sollins P. 1998. Soil carbon and nitrogen pools and processes in an old-growth conifer forest 13 years after trenching. Canadian Journal of Forest Research, 28(8): 1261-1265.
DOI URL |
[15] |
Janssens I A, Freibauer A, Ciais P, et al. 2003. Europe’s terrestrial biosphere absorbs 7% to 12% of European anthropogenic CO2 emissions. Science, 300(5625): 1538-1542.
PMID |
[16] |
Kauppi P E, Mielikäinen K, Kuusela K. 1992. Biomass and carbon budget of European forests, 1971 to 1990. Science, 256(5053): 70-74.
PMID |
[17] |
Lal R. 2005. Forest soils and carbon sequestration. Forest Ecology and Management, 220(1-3): 242-258.
DOI URL |
[18] |
Liski J, Perruchoud D, Karjalainen T. 2002. Increasing carbon stocks in the forest soils of western Europe. Forest Ecology and Management, 169(1-2): 159-175.
DOI URL |
[19] | Liu G H, Fu B J, Fang J Y. 2000. Carbon dynamics of Chinese forests and its contribution to global carbon balance. Acta Ecologica Sinica, 20(5): 733-740. (in Chinese) |
[20] | Luo T X. 1996. The distrubition patterns and modeling of biomass and net primary production in China main forests. Diss., Beijing, China: Chinese Academy of Sciences. (in Chinese) |
[21] |
Luyssaert S, Schulze E D, Börner A, et al. 2008. Old-growth forests as global carbon sinks. Nature, 455(7210): 213-215.
DOI URL |
[22] |
McCarl B A, Metting F B, Rice C. 2007. Soil carbon sequestration. Climatic Change, 80(1-2): 1-3.
DOI URL |
[23] |
Metting F B, Smith J L, Amthor J S, et al. 2001. Science needs and new technology for increasing soil carbon sequestration. Climatic Change, 51(1): 11-34.
DOI URL |
[24] | Pacala S W. 2001. Consistent land- and atmosphere-based US carbon sink estimates. Science, 292(5525): 2316-2320. |
[25] |
Pan Y D, Luo T X, Birdsey R, et al. 2004. New estimates of carbon storage and sequestration in China’s forests: Effects of age-class and method on inventory-based carbon estimation. Climatic Change, 67(2-3): 211-236.
DOI URL |
[26] |
Piao S L, Fang J Y, Ciais P, et al. 2009. The carbon balance of terrestrial ecosystems in China. Nature, 458(7241): 1009-1013.
DOI URL |
[27] |
Raich J W, Nadelhoffer K J. 1989. Belowground carbon allocation in forest ecosystems: Global trends. Ecology, 70(5): 1346-1354.
DOI URL |
[28] |
Schimel D S. 1995. Terrestrial ecosystems and the carbon cycle. Global Change Biology, 1(1): 77-91.
DOI URL |
[29] |
Schlesinger W H. 1990. Evidence from chronosequence studies for a low carbon-storage potential of soils. Nature, 348(6298): 232-234.
DOI URL |
[30] | Schroeder P, Brown S, Mo J M, et al. 1997. Biomass estimation for temperate broadleaf forests of the United States using inventory data. Forest Science, 43(3): 424-434. |
[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] | Tian X R, Shu L F, Wang M Y. 2003. Direct carbon emissions from Chinese forest fires, 1991-2000. Fire Safety Science, 12(1): 6-10. (in Chinese) |
[34] |
Turner D P, Koerper G J, Harmon M E, et al. 1995. A carbon budget for forests of the conterminous United States. Ecological Applications, 5(2): 421-436.
DOI URL |
[35] |
Vermeulen S, Bossio D, Lehmann J, et al. 2019. A global agenda for collective action on soil carbon. Nature Sustainability, 2: 2-4.
DOI |
[36] |
Wang B, Huang J Y, Yang X S, et al. 2010. Estimation of biomass, net primary production and net ecosystem production of China’s forests based on the 1999-2003 National Forest Inventory. Scandinavian Journal of Forest Research, 25(6): 544-553.
DOI URL |
[37] |
Wang S, Chen J M, Ju W M, et al. 2007. Carbon sinks and sources in China’s forests during 1901-2001. Journal of Environmental Management, 85(3): 524-537.
PMID |
[38] | Wang X K, Feng Z W, Zhuang Y H. 2001. CO2, CO and CH4 emissions from forest fires in China. Scientia Silvae Sinicae, 37(1): 90-95. (in Chinese) |
[39] | Wang X K, Zhuang Y H, Feng Z W. 1998. Estimation of carbon-containing gases released from forest fire. Advances in Environmental Science, 6(4): 1-15. (in Chinese) |
[40] |
Wang Y H, Liu K X, Wu Z P, et al. 2020. Comparison and analysis of three estimation methods for soil carbon sequestration potential in the Ebinur Lake Wetland, China. Frontiers of Earth Science, 14(1): 13-24.
DOI URL |
[41] | Wang Y X. 1999. Study on regional carbon cycle of forest ecosystem in China. Diss., Beijing, China: Chinese Academy of Sciences. (in Chinese) |
[42] | Xu X L, Cao M K, Li K R. 2007. Temporal-spatial dynamics of carbon storage of forest vegetation in China. Progress in Geograhpy, 26(6): 1-16. (in Chinese) |
[43] | Yu G R. 2003. Global change, carbon cycle and storage in terrestrial ecosystem. Beijing, China: China Meteorological Press. (in Chinese) |
[44] | Zeng W S, Chen X Y, Pu Y, et al. 2018. Comparison of different methods for estimating forest biomass and carbon storage based on national forest inventory data. Forest Research, 31(1): 66-71. (in Chinese) |
[45] | Zhang Y X. 2006. Change analysis on Chinese forest construction from 1950 to 2003. Journal of Beijing Forestry University, 28(6): 80-87. (in Chinese) |
[46] | Zhao D H, Li J L, Qi J G, et al. 2006. An overview of current methods to estimate carbon budget of terrestrial ecosystems. Acta Ecologica Sinica, 26(8): 2655-2662. (in Chinese) |
[47] |
Zhao M, Zhou G S. 2005. Estimation of biomass and net primary productivity of major planted forests in China based on forest inventory data. Forest Ecology and Management, 207(3): 295-313.
DOI URL |
[48] |
Zhou G S, Wang Y H, Jiang Y L, et al. 2002. Estimating biomass and net primary production from forest inventory data: A case study of China’s Larix forests. Forest Ecology and Management, 169(1-2): 149-157.
DOI URL |
[49] |
Zhou G Y, Liu S G, Li Z A, et al. 2006. Old-growth forests can accumulate carbon in soils. Science, 314(5804): 1417. DOI: 10.1126/science.1130168.
DOI URL |
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