摘要: 目的建立全国单木材积生物量模型非常重要且必要。研究中国的森林碳储量变化及其碳汇能力对于估算区域碳收支和制定应对气候变化的森林管理政策具有重要意义、�/sec> 方法本文结合森林资源清查抽样总体和气候区差异的实际，利用全国森林资源清查22种主要树种的生物量建模实测数据，分别建立区域性单木生物量与材积回归模型，利用1949�?018年间11个时间段的森林资源清查和统计数据，系统测算出了近70年全国及各个区域森林碳储量和碳源汇能力，以期揭示�?0年来我国森林碳储量的变化规律和原因以及对碳汇的相关贡献、�/sec> 结果研究结果表明：在1949�?018年间，林分、疏林等森林资源碳储总量�?.509 × 10 ¹²kg增加�?.601 × 10 ¹²kg，增加了90.74%，其�?014�?018年期间年均增�?.09%；林分碳储量�?.38 × 10 ¹²kg增加�?.97 × 10 ¹²kg，增加了81.97%；林分碳密度�?973�?976年时段最低为31.64 t/hm ²�?014�?018年时段增加到44.30 t/hm ²，但是仍然没有达�?949年的46.48 t/hm ²；各区域的森林资源碳储总量都有不同程度的增加，尤其是华北区和东南沿海区增长较快，分别增加了145.91%�?16.63%；全国及各个区域的森林碳储量和碳密度的变化规律基本呈现出先下降后增加的趋势。全国碳源汇的变化规律也与此基本相同�?981年之前，年均碳积累是负值，以碳源为主，1981年之后碳积累是正值，年均生物量碳�?.122 × 10 ¹²kg/a，且积累能力不断提高。林分生物量碳库在森林总碳库中占据主要地位，各期的全国林分碳储量占碳储总量的比例均�?0%以上；由于我国人工林面积大量增加，碳累积增长速度很快，自20世纪70年代以来年均生物量碳汇为0.04 × 10 ¹²kg/a；天然林�?989年前虽然碳累积为负值，但自我国实行天然林保护工程以来，天然林碳汇能力持续增强，是我国森林碳逐年累积的主要贡献者、�/sec> 结论随着我国全面实施天然林保护、生态修复和保护政策持续加强，同时中国现阶段以中幼龄林为主的森林已进入快速增长期，因此未来中国的森林碳汇潜力巨大、�/sec>

关键诌�
• 森林资源/
• 森林资源清查/
• 生物量碳庒�/a> /
• 碳储野�/a> /
• 碳汇

Abstract: ObjectiveIt is very important and necessary to establish the national single tree volume biomass model. The research on forest carbon storage change and carbon sequestration capacity has great significance to the forest management policies of estimating regional carbon balance and addressing climate change. MethodWith forest resource sampling population and the difference of climate zones, using the survey data from 22 main forest type biomass building models in national forest inventory, establishing regional individual tree regression models of biomass and stock volume, using 11 periods of forest inventory and statistics data from 1949 to 2018, the paper calculates forest carbon storage and carbon sequestration capacity in 70 forest regions to explore forest carbon storage change regulations, causes and contribution to carbon sequestration in 70 years. ResultFrom 1949 to 2018, forest carbon storage of forest stand and sparse forest increased from 4.509 × 10 ¹²to 8.601 × 10 ¹²kg, increased by 90.74%. Average annual increase was 3.09% during 2014 to 2019; carbon storage of forest storage increased from 4.38 × 10 ¹²to 7.97 × 10 ¹²kg, increased by 81.97%; the lowest carbon intensity of forest stand from 1973 to 1976 was 31.64 t/ha, and increased to 44.30 t/ha from 2014 to 2018, but it cannot reach 46.48 t/ha in 1949. Forest carbon storage in different regions increased differently. Forest carbon storage in north China and southeast coast regions increased by 145.91% and 116.63%, respectively. National and regional forest carbon storage and carbon intensity showed the trends of firstly decreased and secondly increased. The national forest showed the same trends. Before 1981, annual average of carbon accumulation was negative and it was carbon source. After 1981, carbon accumulation was positive. Annual average of biomass carbon sequestration was 0.122 × 10 ¹²kg/year, and carbon accumulation increased gradually. Carbon storage of forest stand accounted for the main parts of forest resource, and its carbon storage was more than 80% of total forest carbon storage. As plantation forest area increased in large proportion and its carbon accumulation increased quickly, annual average biomass carbon sequestration had been 0.04 × 10 ¹²kg/year since 1970s; before 1989, natural forest carbon accumulation was negative, but its carbon sequestration capacity had been increased continually since national forest protection program. It was the main contributor to annual forest carbon accumulation. ConclusionWith national forest protection, ecosystem restoration and protection, and the dominated middle and young age forest stand had entered into quick growing period. The potential of forest carbon sequestration in China will be great.

Key words:
• forest resource/
• forest resource inventory/
• biomass carbon pool/
• carbon storage/
• carbon sequestration

�?nbsp; 1不同区域生物量转换因子（BEF）与根茎比（RSR）比辂�/p>

Figure 1.Comparison of BEF and RSR values in different regions

下载: 全尺寸图牆�/a> 幻灯牆�/a>

�?nbsp; 2两种测算方法地上生物量结果对毓�/p>

BJ为北京；TJ为天津；HB为河北；SX为山西；NM为内蒙古；LN为辽宁；JL为吉林；HLJ为黑龙江；SH为上海；JS为江苏；ZJ为浙江；AH为安徽；FJ为福建；JX为江西；SD为山东；HN为河南；HUB为湖北；HUN为湖南；GD为广东；GX为广西；HNN为海南；CQ为重庆；SC为四川；GZ为贵州；YN为云南；XZ为西藏；SHX为陕西；GS为甘肃；QH为青海；NX为宁夏；XJ为新疆。BJ, Beijing City; TJ, Tianjing City; HB, Hebei Province; SX, Shanxi Province; NM, Inner Mongolia Autonomous Region; LN, Liaoning Province; JL, Jilin Province; HLJ, Heilongjiang Province; SH, Shanghai City; JS, Jiangshu Province; ZJ, Zhejiang Province; AH, Anhui Province; FJ, Fujian Province; JX, Jiangxi Province; SD, Shandong Province; HN, Henan Province; HUB, Hubei Province; HUN, Hunan Province; GD, Guangdong Province; GX, Guangxi Zhuang Autonomous Region; HNN, Hainan Province; CQ, Chongqing City; SC, Sichuan Province; GZ, Guizhou Province; YN, Yunnan Province, XZ, Tibet; SHX, Shaanxi Province; GS, Gansu Province; QH, Qinhai Province; NX, Ningxia Hui Autonomous Region; XJ, Xinjiang Uygur Autonomous Region.

Figure 2.Comparison of aboveground biomass results by two calculating methods

下载: 全尺寸图牆�/a> 幻灯牆�/a>

�?nbsp; 3各时期森林碳储量和碳密度变化

数字1 ~ 11代表研究时间段，依次为：1949�?950�?962�?973�?976�?977�?981�?984�?988�?989�?993�?994�?998�?999�?003�?004�?008�?009�?013�?014�?018年。下同。The No. 1�?1 represent the periods of year 1949, 1950�?962, 1973�?976, 1977�?981, 1984�?988, 1989�?993, 1994�?998, 1999�?003, 2004�?008, 2009�?013, 2014�?018, respectively. The same below.

Figure 3.Changes of forest carbon storage and carbon density in different periods

下载: 全尺寸图牆�/a> 幻灯牆�/a>

�?nbsp; 41949�?018年森林面积、蓄积量、碳储量、碳密度和碳储总量变化

Figure 4.Changes of forest area, volume stock, carbon storage, carbon density and total carbon storage from 1949 to 2018

下载: 全尺寸图牆�/a> 幻灯牆�/a>

�?nbsp; 1全国主要树种材积与生物量模型

Table 1.Regression model of volume to biomass of main tree species in China

建模范围 Modeling range	建模树种(�? Modeling tree species (group)	地上生物量与材积 Aboveground biomass and volume				地下与地上生物量 Underground biomass and aboveground biomass
		模型表达弎�br/>Model expression	N	R2		模型表达弎�br/>Model expression	N	R2
CH	柳杉Cryptomeria fortunei	Y1= 0.917 2X10.872 5	150	0.991 9		Y2= 0.224 5X21.061 0	47	0.962 7
	马尾�Pinus massoniana	Y1= 0.806 7X10.948 3	301	0.989 6		Y2= 0.119 8X21.081 2	104	0.973 8
	杉木Cunninghamia lanceolata	Y1= 0.684 6X10.908 9	301	0.987 8		Y2= 0.240 8X20.983 9	102	0.953 3
	油松Pinus tabuliformis	Y1= 0.840 0X10.958 4	149	0.983 9		Y2= 0.189 2X21.041 2	49	0.965 2
	黄山�Pinus taiwanensis	Y1= 0.686 1X10.966 0	150	0.988 6		Y2= 0.189 1X20.981 1	51	0.955 6
NE	落叶�Larix dahurica	Y1= 0.762 9X10.947 7	150	0.994 2		Y2= 0.199 9X21.091 1	50	0.979 1
	云杉Picea asperata	Y1= 0.799 1X10.952 0	150	0.986 4		Y2= 0.270 4X20.970 7	50	0.964 6
	冷杉Abies fabri	Y1= 0.624 5X10.974 8	150	0.992 7		Y2= 0.223 4X20.983 3	49	0.977 3
	栎树Quercusspp.	Y1= 0.851 7X11.009 0	160	0.989 2		Y2= 0.545 7X20.864 4	53	0.948 2
	白桦Betula platyphylla	Y1= 0.668 2X11.005 9	150	0.994 9		Y2= 0.362 2X20.956 1	53	0.966 8
	桦树Betulaspp.	Y1= 0.514 6X11.046 7	150	0.985 3		Y2= 0.438 1X20.895 4	51	0.941 1
	山杨Populus davidiana	Y1= 0.621 6X10.978 3	151	0.991 5		Y2= 0.237 8X20.975 0	55	0.971 6
	人工�Populus simonii	Y1= 0.692 5X10.947 2	150	0.988 1		Y2= 0.284 3X20.949 9	50	0.943 6
	樟子�Pinus sylvestrisvar.mongolica	Y1= 0.578 3X10.956 1	151	0.981 7		Y2= 0.335 3X21.121 9	49	0.939 6
	椴树Tilia tuan	Y1= 0.463 9X11.024 5	150	0.983 3		Y2= 0.871 6X21.006 0	50	0.934 0
	榆树Ulmus pumila	Y1= 0.781 4X11.009 4	149	0.988 7		Y2= 0.709 0X21.028 6	49	0.993 6
NN、NW	落叶�Larix dahurica	Y1= 0.733 8X10.935 1	300	0.983 5		Y2= 0.285 9X20.963 3	100	0.957 0
	云杉Picea asperata	Y1= 0.913 0X10.9128	300	0.978 6		Y2= 0.300 5X20.958 7	100	0.940 7
	冷杉Abies fabri	Y1= 0.696 8X10.957 0	150	0.987 5		Y2= 0.206 6X21.013 4	50	0.968 4
	柏木Cupressus funebris	Y1= 1.133 7X10.9422	300	0.971 5		Y2= 0.339 7X20.921 3	102	0.924 4
	栎树Quercusspp.	Y1= 0.719 3X11.029 6	210	0.972 3		Y2= 0.495 5X20.869 8	72	0.936 6
	桦树Betulaspp.	Y1= 0.855 1X10.979 1	240	0.969 1		Y2= 0.335 9X20.941 4	79	0.961 1
	人工�Populus simonii	Y1= 0.611 6X11.001 6	150	0.990 4		Y2= 0.304 2X20.931 4	48	0.990 1
	山杨Populus davidiana	Y1= 0.631 0X10.998 7	150	0.988 5		Y2= 0.281 6X20.951 6	55	0.974 9
WS	云杉Picea asperata	Y1= 0.818 1X10.927 3	302	0.967 0		Y2= 0.211 5X21.009 8	98	0.961 5
	冷杉Abies fabri	Y1= 0.690 1X10.939 9	301	0.985 5		Y2= 0.282 5X20.948 3	101	0.950 8
XZ	云杉Picea asperata	Y1= 0.943 8X10.919 1	149	0.961 7		Y2= 0.196 3X20.983 1	47	0.960 4
	冷杉Abies fabri	Y1= 0.607 3X10.950 6	150	0.986 2		Y2= 0.190 3X21.033 0	49	0.979 7
WS、XZ	落叶�Larix dahurica	Y1= 0.716 8X10.929 3	152	0.982 4		Y2= 0.190 1X21.006 6	49	0.946 2
	栎树Quercusspp.	Y1= 1.086 4X10.935 8	151	0.980 0		Y2= 0.372 5X20.883 9	50	0.953 8
	桦树Betulaspp.	Y1= 0.692 6X10.987 1	150	0.977 6		Y2= 0.261 7X20.978 3	53	0.944 6
	云南�Pinus yunnanensis	Y1= 0.536 0X10.993 8	150	0.986 7		Y2= 0.155 3X21.007 7	50	0.973 1
	山杨Populus davidiana	Y1= 0.642 3X10.977 2	150	0.994 1		Y2= 0.275 0X20.912 3	50	0.974 5
	思茅�Pinus kesiyavar.langbianensis	Y1= 0.391 8X11.060 3	150	0.994 7		Y2= 0.170 1X20.984 2	49	0.986 4
	高山�Pinus densata	Y1= 0.786 5X10.958 5	150	0.982 6		Y2= 0.156 2X21.030 6	49	0.934 9
	柏木Cupressus funebris	Y1= 1.020 3X10.931 2	150	0.991 7		Y2= 0.232 6X20.936 4	51	0.973 0
MS、ES	湿地�Pinus elliottii	Y1= 0.677 4X10.980 1	154	0.991 9		Y2= 0.388 9X20.917 3	50	0.937 2
	柏木Cupressus funebris	Y1= 0.949 6X10.950 4	160	0.985 6		Y2= 0.216 7X21.011 0	65	0.973 0
	栎树Quercusspp.	Y1= 1.228 2X10.934 1	149	0.982 8		Y2= 0.324 2X20.921 9	53	0.905 9
	木荷Schima superba	Y1= 0.857 3X10.975 3	150	0.993 7		Y2= 0.294 0X20.992 0	50	0.959 0
	枫香Liquidambar formosana	Y1= 0.793 6X10.993 1	152	0.991 0		Y2= 0.463 2X20.933 9	50	0.966 6
	人工�Populus simonii	Y1= 0.545 8X11.019 9	151	0.995 3		Y2= 0.221 9X20.933 7	49	0.975 0
注：CH为全国；NE为东北区；NN为华北区；NW为西北区；MS为中南区；ES为东南沿海区；WS为西南区；XZ为西藏区：�i>N为原始数据样本数量，R2为决定系数；Y1为单木生物量(地上部分)(t)＋�i>X1为单木材�?m3)：�i>Y2为单木地下生物量(t)�X2为单木地上生物量(t)。下同。Notes: CH, whole country; NE, Northeast China; NN, North China; NW, Northwest China; MS, South Central China; ES, Southeast Coastal China; WS, Southwest China; XZ is Tibet;N, sample number of raw data;R2, coefficient of determination;Y1, biomass of a tree (aboveground) (t);X1, volume of single tree (m3);Y2, underground biomass of a tree (t);X2, aboveground biomass of a tree (t). The same below.

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�?nbsp; 2全国各区域按森林类型建立的材积与生物量回归模垊�/p>

Table 2.Regression models of volume to biomass by forest types in different regions of China

适用范围 Scope of application	建模树种(�? Modeling tree species (group)	地上生物量与材积 Aboveground biomass and volume				地下与地上生物量 Underground biomass and aboveground biomass
		模型表达� Model expression	N	R2		模型表达� Model expression	N	R2
NE	A	Y1= 0.683 9X10.965 7	600	0.987 5		Y2= 0.257 9X21.035 3	199	0.938 9
	B	Y1= 1.368 1X10.946 0	1 060	0.943 9		Y2= 0.468 9X20.949 0	361	0.882 7
	C	Y1= 1.114 3X10.941 8	1 660	0.940 7		Y2= 0.382 1X20.977 9	560	0.898 6
NN	A	Y1= 0.995 5X10.935 5	449	0.970 8		Y2= 0.277 2X20.963 3	150	0.952 9
	B	Y1= 0.745 0X11.001 2	600	0.972 7		Y2= 0.373 0X20.941 9	199	0.957 0
	C	Y1= 0.843 7X10.974 0	1 049	0.970 9		Y2= 0.328 2X20.934 9	349	0.954 2
NW	A	Y1= 0.880 3X10.920 6	600	0.974 1		Y2= 0.293 8X20.960 6	201	0.936 7
	B	Y1= 0.752 1X11.000 1	600	0.972 4		Y2= 0.364 1X20.919 9	206	0.953 3
	C	Y1= 0.821 5X10.957 1	1 200	0.970 0		Y2= 0.329 5X20.938 3	407	0.944 8
MS	A	Y1= 0.853 9X10.936 9	433	0.982 2		Y2= 0.223 8X21.002 0	149	0.956 2
	B	Y1= 0.829 7X10.977 4	320	0.978 3		Y2= 0.229 2X20.919 7	109	0.924 3
	C	Y1= 0.841 6X10.954 8	753	0.979 0		Y2= 0.253 0X20.965 6	258	0.941 8
ES	A	Y1= 0.737 4X10.951 1	774	0.981 5		Y2= 0.220 5X20.998 8	255	0.956 7
	B	Y1= 0.970 3X10.964 2	341	0.985 2		Y2= 0.318 4X20.955 5	115	0.940 4
	C	Y1= 0.800 6X10.955 6	1 115	0.977 8		Y2= 0.245 3X20.987 4	370	0.949 7
WS	A	Y1= 0.712 8X10.945 0	1 337	0.978 2		Y2= 0.199 5X21.004 4	446	0.959 0
	B	Y1= 0.803 0X10.968 0	501	0.980 0		Y2= 0.310 7X20.931 7	171	0.944 9
	C	Y1= 0.738 3X10.950 5	1 838	0.976 6		Y2= 0.224 0X20.985 5	617	0.953 3
XZ	A	Y1= 0.759 8X10.946 6	569	0.971 8		Y2= 0.185 4X20.990 4	186	0.950 6
	B	Y1= 0.642 3X10.977 2	150	0.994 1		Y2= 0.275 0X20.912 3	50	0.974 5
	C	Y1= 0.734 0X10.953 0	719	0.976 4		Y2= 0.204 0X20.971 1	236	0.953 9
注：A为针叶树种；B为阔叶树种；C为针阔混交树种。下同。Notes: A, coniferous tree species; B, broadleaved tree species; C, coniferous and broadleaved mixed tree species. The same below.

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�?nbsp; 3各区域各森林类型的生物量转换因子（BEF）和根茎比（RSR）比辂�/p>

Table 3.Comparison of biomass expansion factor (BEF) and root-to-shoot ratio (RSR) of different forest types in different regions

区域 Region	类型 Type	变量 Variable	样本�?br/>Sample number	平均倻�br/>Average value	最小倻�br/>Min. value	最大倻�br/>Max. value	标准�?br/>SD	变动系数 Coefficient of variation/%
NE	A	BEF/(g·cm�?)	600	0.614	0.176	1.510	0.169	27.6
		RSR	199	0.354	0.079	2.581	0.289	81.8
	B	BEF/(g·cm�?)	1 060	0.675	0.040	3.561	0.215	31.9
		RSR	361	0.574	0.074	3.587	0.471	82.1
	C	BEF/(g·cm�?)	1 660	0.653	0.040	3.561	0.202	31.0
		RSR	560	0.496	0.074	3.587	0.429	86.5
NN	A	BEF/(g·cm�?)	449	0.834	0.295	3.041	0.322	38.6
		RSR	150	0.267	0.059	0.960	0.126	47.2
	B	BEF/(g·cm�?)	600	0.795	0.139	2.087	0.282	35.4
		RSR	199	0.303	0.036	1.200	0.162	53.5
	C	BEF/(g·cm�?)	1 049	0.812	0.139	3.041	0.300	37.0
		RSR	349	0.288	0.036	1.200	0.149	51.6
NW	A	BEF/(g·cm�?)	600	0.681	0.165	3.311	0.300	44.1
		RSR	201	0.287	0.052	1.351	0.154	53.6
	B	BEF/(g·cm�?)	600	0.799	0.139	2.087	0.282	35.3
		RSR	206	0.302	0.036	1.200	0.163	53.9
	C	BEF/(g·cm�?)	1 200	0.740	0.139	3.311	0.297	40.1
		RSR	407	0.295	0.036	1.351	0.158	53.8
MS	A	BEF/(g·cm�?)	433	0.699	0.200	6.236	0.338	48.4
		RSR	149	0.254	0.073	1.347	0.164	64.5
	B	BEF/(g·cm�?)	320	0.804	0.389	2.287	0.310	38.6
		RSR	109	0.430	0.033	1.301	0.247	57.4
	C	BEF/(g·cm�?)	753	0.744	0.200	6.236	0.330	44.4
		RSR	258	0.329	0.033	1.347	0.221	67.2
ES	A	BEF/(g·cm�?)	774	0.637	0.242	6.236	0.279	43.7
		RSR	255	0.243	0.065	0.838	0.120	49.1
	B	BEF/(g·cm�?)	341	0.874	0.396	2.287	0.279	31.9
		RSR	115	0.308	0.033	1.200	0.181	58.6
	C	BEF/(g·cm�?)	1 115	0.710	0.242	6.236	0.299	42.2
		RSR	370	0.264	0.033	1.200	0.144	54.7
WS	A	BEF/(g·cm�?)	1 337	0.603	0.134	2.428	0.227	37.6
		RSR	446	0.225	0.059	0.912	0.115	51.1
	B	BEF/(g·cm�?)	501	0.741	0.202	2.118	0.251	33.9
		RSR	171	0.273	0.020	0.954	0.141	51.6
	C	BEF/(g·cm�?)	1838	0.641	0.134	2.428	0.242	37.8
		RSR	617	0.238	0.020	0.954	0.125	52.3
XZ	A	BEF/(g·cm�?)	569	0.656	0.213	1.972	0.276	42.1
		RSR	186	0.199	0.045	0.559	0.093	47.0
	B	BEF/(g·cm�?)	150	0.593	0.295	1.309	0.114	19.2
		RSR	50	0.217	0.113	0.527	0.099	45.6
	C	BEF/(g·cm�?)	719	0.643	0.213	1.972	0.253	39.3
		RSR	236	0.203	0.045	0.559	0.095	46.8

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�?nbsp; 41949�?018年不同时期森林面积、蓄积、碳储量及年均碳累积

Table 4.Forest area, volume, carbon storage and annual average carbon sequestration in different periods from 1949 to 2018

调查朞�br/>Investigating period	林分 Stand					人工� Plantation					天然� Natural forest
	FA	FV	FC	AC		FA	FV	FC	AC		FC	FV	FC	AC
1949	94.23	92.23	4.38	–�/td>		–�/td>	–�/td>	–�/td>	–�/td>		–�/td>	–�/td>	–�/td>	–�/td>
1950�?962	95.85	83.67	3.98	�?.033		–�/td>	–�/td>	–�/td>	–�/td>		–�/td>	–�/td>	–�/td>	–�/td>
1973�?976	119.78	84.70	3.79	�?.014		17.81	1.64	0.07			101.97	83.06	3.72
1977�?981	95.63	79.79	3.69	�?.020		12.73	2.73	0.13	0.011		82.90	77.06	3.56	�?.031
1984�?988	102.19	80.91	3.71	0.003		18.74	5.30	0.24	0.017		83.45	75.61	3.47	�?.014
1989�?993	108.64	90.87	4.08	0.074		21.37	7.12	0.32	0.015		87.27	83.75	3.76	0.059
1994�?998	129.20	100.86	4.56	0.096		19.14	10.13	0.46	0.028		110.06	90.73	4.10	0.068
1999�?003	142.79	120.98	5.43	0.174		32.29	15.05	0.68	0.044		110.50	105.93	4.75	0.130
2004�?008	155.59	133.63	6.10	0.134		40.00	19.61	0.90	0.044		115.59	114.02	5.20	0.090
2009�?013	164.60	147.79	6.81	0.142		47.07	24.83	1.14	0.050		117.53	122.96	5.67	0.092
2014�?018	179.89	170.58	7.97	0.232		57.13	33.88	1.58	0.088		122.76	136.70	6.39	0.144
注：1949年和1950�?962年两期资源数据不含西藏自治区的数据，1977�?981�?984�?988�?989�?993�?994�?998�?期数据统计不含西藏控制以外；FA为森林面�?106hm2)，FV为森林蓄�?108m3)，FC为碳储量(1012kg)，AC为年均碳累积(1012kg/a)；—表示没有调查统计数据。下同。Notes: The resource data for the periods of year 1949 and 1950�?962 do not include Tibet’s data, and data statistics for the periods of year 1977�?981, 1984�?988, 1989�?993 and 1994�?998 do not include data outside of Tibetan control; FA, forest area (106ha); FV, forest volume (108m3); FC, carbon storage (1012kg); AC, annual average carbon sequestration (1012kg/year); � indicates no survey statistic data. The same below.

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�?nbsp; 5全国各区域林分、疏林等碳储量占碳储总量的百分比

Table 5.Percentage of carbon storage in total carbon storage of forest and sparse forest in different regions of China %

区域 Region	组分 Component	1949	1950�?962	1973�?976	1977�?981	1984�?988	1989�?993	1994�?998	1999�?003	2004�?008	2009�?013	2014�?018
NE	SF	0.97	5.91	6.20	7.48	9.49	10.59	10.55	10.20	6.51	6.15	6.93
	FL	99.03	94.09	93.80	92.52	90.51	89.41	89.45	89.80	93.49	93.85	93.07
NN	SF	0.66	10.87	15.20	13.83	15.84	22.07	21.39	17.14	13.87	10.45	8.27
	FL	99.34	89.13	84.80	86.17	84.16	77.93	78.61	82.86	86.13	89.55	91.73
NW	SF	28.78	9.27	14.11	11.92	14.94	16.87	13.04	12.22	9.11	9.70	9.37
	FL	71.22	90.73	85.89	88.08	85.06	83.13	86.96	87.78	90.89	90.30	90.63
MS	SF	3.95	11.46	28.04	28.94	31.47	34.44	32.01	22.02	15.75	16.35	12.56
	FL	96.05	88.54	71.96	71.06	68.53	65.56	67.99	77.98	84.25	83.65	87.44
ES	SF	0.00	11.41	21.59	21.78	22.60	18.44	14.85	12.47	9.38	9.39	7.51
	FL	100.00	88.59	78.41	78.22	77.40	81.56	85.15	87.53	90.62	90.61	92.49
WS	SF	0.00	7.78	13.46	15.21	15.58	29.34	10.93	11.54	8.70	8.84	6.77
	FL	100.00	92.22	86.54	84.79	84.42	70.66	89.07	88.46	91.30	91.16	93.23
XZ	SF	–�/td>	–�/td>	0.00	6.27	0.00	2.70	4.30	1.26	1.19	1.13	0.94
	FL	–�/td>	–�/td>	100.00	93.73	100.00	97.30	95.70	98.74	98.81	98.87	99.06
CH	SF	2.89	8.57	12.19	14.20	15.36	16.13	14.01	11.61	8.76	8.58	7.35
	FL	97.11	91.43	87.81	85.80	84.64	83.87	85.99	88.39	91.24	91.42	92.65
注：SF为疏林等，FL为林分。Notes: SF, sparse forest, etc; FL, stand.

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�?nbsp; 6全国不同时期森林碳密度　　　　　　　　　　　　　　　　　　t/hm²

Table 6.Changes in forest carbon density in different periods of China t/ha

区域 Region	1949	1950�?962	1973�?976	1977�?981	1984�?988	1989�?993	1994�?998	1999�?003	2004�?008	2009�?013	2014�?018
CH	46.48	42.20	31.64	38.61	36.30	37.60	35.26	38.04	39.19	41.38	44.30
NE	50.81	47.83	42.71	45.47	42.88	43.64	41.68	41.03	41.97	44.69	48.73
NN	40.37	39.81	27.27	31.42	31.53	31.43	31.62	30.92	31.12	34.57	37.89
NW	42.75	49.28	39.25	42.99	39.54	43.56	41.75	43.24	42.77	43.46	46.45
MS	28.18	21.54	10.95	17.94	18.44	19.23	18.54	22.30	24.68	27.82	31.83
ES	38.97	34.21	14.95	29.16	24.30	23.31	21.96	26.81	30.64	33.29	39.27
WS	62.59	54.12	45.30	52.91	48.51	47.50	43.25	43.79	45.03	46.78	46.39
XZ	–�/td>	–�/td>	76.05	58.89	58.89	96.75	95.97	90.88	92.10	91.87	88.65

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�?nbsp; 7本文碳储量与其他研究结果的对毓�/p>

Table 7.Comparison of carbon storage results between this study and other research 10 ¹²kg

调查朞�br/>Investigating period	本文 This study			方精云等[1] Fang J Y, et al.[1]		方精云等[12,30] Fang J Y, et al.[12,30]		郭兆迪等[40] Guo Z D, et al.[40]		Zhang C H, et al.[24]			朱永�?sup>[39] Zhu Y J[39]		李妍筈�sup>[41] Li Y, et al.[41]
	林分 Stand	森林资源 Forest resource		林分 Stand		林分 Stand		林分 Stand		林分 Stand	森林资源 Forest resource		林分 Stand		林分 Stand
1949	4.38	4.51		5.06		–�/td>		–�/td>		–�/td>	–�/td>		–�/td>		–�/td>
1950�?962	3.98	4.35		4.58		–�/td>		–�/td>		–�/td>	–�/td>		–�/td>		–�/td>
1973�?976	3.79	4.32		4.44		–�/td>		–�/td>		4.11	4.38		–�/td>		3.85
1977�?981	3.69	4.30		4.38		4.30		4.72		4.21	4.75		4.09		3.70
1984�?988	3.71	4.38		4.45		4.46		4.89		4.18	4.82		4.04		3.76
1989�?993	4.08	4.87		4.63		4.93		5.40		4.52	5.25		4.76		4.11
1994�?998	4.56	5.30		4.75		5.01		5.39		4.50	5.12		5.25		4.66
1999�?003	5.43	6.15		–�/td>		5.85		5.86		5.41	5.97		6.49		5.51
2004�?008	6.10	6.68		–�/td>		–�/td>		6.43		6.24	6.83		7.895		6.09
2009�?013	6.81	7.45		–�/td>		–�/td>		–�/td>		–�/td>	–�/td>		–�/td>		–�/td>
2014�?018	7.97	8.60		–�/td>		–�/td>		–�/td>		–�/td>	–�/td>		–�/td>		–�/td>

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