1949—2018年中国森林资源碳储量变化研究

张煜星; 王雪军; 蒲莹; 张建波

doi:10.12171/j.1000-1522.20200237

1949—2018年中国森林资源碳储量变化研究

张煜星^1,,
王雪军^2, ,,
蒲莹³,
张建波⁴

1.
国家林业和草原局林产工业规划设计院，北京 100714
2.
国家林业和草原局森林资源管理司，北京 100714
3.
国家林业和草原局调查规划设计院，北京 100714
4.
内蒙古自治区林业和草原监测规划院，内蒙古呼和浩特 010011

基金项目: 国家重点研发项目（2017YFD0600903），全国森林资源清查生物量基础建模项目（LY2014-2018）

详细信息

作者简介:
张煜星，博士，教授级高级工程师。主要研究方向：森林资源监测和森林碳汇。Email：mrqzyx@sina.com　地址：100714北京市东城区朝阳门内大街130号国家林业和草原局林产工业规划设计院

责任作者:
王雪军，博士，教授级高级工程师。主要研究方向：森林资源监测与评价。Email：wangxuejun320@126.com　地址：100714北京市东城区和平里东街18号国家林业和草原局森林资源管理司

中图分类号: S750
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出版历程
- 收稿日期: 2020-07-28
- 修回日期: 2020-09-13
- 网络出版日期: 2021-05-11
- 发布日期: 2021-05-26

Changes in forest resource carbon storage in China between 1949 and 2018

1.
Academy of Forest Industry Design and Planning, National Forestry and Grassland Administration, Beijing 100714, China
2.
Forest Resource Management Department, National Forestry and Grassland Administration, Beijing 100714, China
3.
Academy of Forest and Grassland Inventory and Planning, National Forestry and Grassland Administration, Beijing 100714, China
4.
Inner Mongolia Forest and Grassland Monitoring and Planning Institute, Hohhot 010011, Inner Mongolia, China

摘要

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。
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—2018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，以期揭示出70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。
结果研究结果表明：在1949—2018年间，林分、疏林等森林资源碳储总量由4.509 × 10¹² kg增加到8.601 × 10¹² kg，增加了90.74%，其中2014—2018年期间年均增长3.09%；林分碳储量由4.38 × 10¹² kg增加到7.97 × 10¹² kg，增加了81.97%；林分碳密度在1973—1976年时段最低为31.64 t/hm²，2014—2018年时段增加到44.30 t/hm²，但是仍然没有达到1949年的46.48 t/hm²；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%和116.63%；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，1981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，年均生物量碳汇0.122 × 10¹² kg/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在80%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 × 10¹² kg/a；天然林在1989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。
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。
- 森林资源 /
- 森林资源清查 /
- 生物量碳库 /
- 碳储量 /
- 碳汇
Abstract:
Objective It 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.
Method With 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.
Result From 1949 to 2018, forest carbon storage of forest stand and sparse forest increased from 4.509 × 10¹² to 8.601 × 10¹² kg, increased by 90.74%. Average annual increase was 3.09% during 2014 to 2019; carbon storage of forest storage increased from 4.38 × 10¹² to 7.97 × 10¹² kg, 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 × 10¹² kg/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 × 10¹² kg/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.
Conclusion With 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.
- forest resource /
- forest resource inventory /
- biomass carbon pool /
- carbon storage /
- carbon sequestration

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图 1 不同区域生物量转换因子（BEF）与根茎比（RSR）比较

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

下载: 全尺寸图片幻灯片

图 2 两种测算方法地上生物量结果对比

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

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图 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、1950—1962、1973—1976、1977—1981、1984—1988、1989—1993、1994—1998、1999—2003、2004—2008、2009—2013、2014—2018年。下同。The No. 1−11 represent the periods of year 1949, 1950−1962, 1973−1976, 1977−1981, 1984−1988, 1989−1993, 1994−1998, 1999−2003, 2004−2008, 2009−2013, 2014−2018, respectively. The same below.

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

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图 4 1949—2018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

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表 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(组) 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
建模范围 Modeling range	建模树种(组) Modeling tree species (group)	模型表达式 Model expression	N	R²	模型表达式 Model expression	N	R²
CH	柳杉 Cryptomeria fortunei	Y₁ = 0.917 2X₁^{0.872 5}	150	0.991 9	Y₂ = 0.224 5X₂^{1.061 0}	47	0.962 7
	马尾松 Pinus massoniana	Y₁ = 0.806 7X₁^{0.948 3}	301	0.989 6	Y₂ = 0.119 8X₂^{1.081 2}	104	0.973 8
	杉木 Cunninghamia lanceolata	Y₁ = 0.684 6X₁^{0.908 9}	301	0.987 8	Y₂ = 0.240 8X₂^{0.983 9}	102	0.953 3
	油松 Pinus tabuliformis	Y₁ = 0.840 0X₁^{0.958 4}	149	0.983 9	Y₂ = 0.189 2X₂^{1.041 2}	49	0.965 2
	黄山松 Pinus taiwanensis	Y₁ = 0.686 1X₁^{0.966 0}	150	0.988 6	Y₂ = 0.189 1X₂^{0.981 1}	51	0.955 6
NE	落叶松 Larix dahurica	Y₁ = 0.762 9X₁^{0.947 7}	150	0.994 2	Y₂ = 0.199 9X₂^{1.091 1}	50	0.979 1
	云杉 Picea asperata	Y₁ = 0.799 1X₁^{0.952 0}	150	0.986 4	Y₂ = 0.270 4X₂^{0.970 7}	50	0.964 6
	冷杉 Abies fabri	Y₁ = 0.624 5X₁^{0.974 8}	150	0.992 7	Y₂ = 0.223 4X₂^{0.983 3}	49	0.977 3
	栎树 Quercus spp.	Y₁ = 0.851 7X₁^{1.009 0}	160	0.989 2	Y₂ = 0.545 7X₂^{0.864 4}	53	0.948 2
	白桦 Betula platyphylla	Y₁ = 0.668 2X₁^{1.005 9}	150	0.994 9	Y₂ = 0.362 2X₂^{0.956 1}	53	0.966 8
	桦树 Betula spp.	Y₁ = 0.514 6X₁^{1.046 7}	150	0.985 3	Y₂ = 0.438 1X₂^{0.895 4}	51	0.941 1
	山杨 Populus davidiana	Y₁ = 0.621 6X₁^{0.978 3}	151	0.991 5	Y₂ = 0.237 8X₂^{0.975 0}	55	0.971 6
	人工杨 Populus simonii	Y₁ = 0.692 5X₁^{0.947 2}	150	0.988 1	Y₂ = 0.284 3X₂^{0.949 9}	50	0.943 6
	樟子松 Pinus sylvestris var. mongolica	Y₁ = 0.578 3X₁^{0.956 1}	151	0.981 7	Y₂ = 0.335 3X₂^{1.121 9}	49	0.939 6
	椴树 Tilia tuan	Y₁ = 0.463 9X₁^{1.024 5}	150	0.983 3	Y₂ = 0.871 6X₂^{1.006 0}	50	0.934 0
	榆树 Ulmus pumila	Y₁ = 0.781 4X₁^{1.009 4}	149	0.988 7	Y₂ = 0.709 0X₂^{1.028 6}	49	0.993 6
NN、NW	落叶松 Larix dahurica	Y₁ = 0.733 8X₁^{0.935 1}	300	0.983 5	Y₂ = 0.285 9X₂^{0.963 3}	100	0.957 0
	云杉 Picea asperata	Y₁ = 0.913 0X₁^0.9128	300	0.978 6	Y₂ = 0.300 5X₂^{0.958 7}	100	0.940 7
	冷杉 Abies fabri	Y₁ = 0.696 8X₁^{0.957 0}	150	0.987 5	Y₂ = 0.206 6 X₂^{1.013 4}	50	0.968 4
	柏木 Cupressus funebris	Y₁ = 1.133 7X₁^0.9422	300	0.971 5	Y₂ = 0.339 7X₂^{0.921 3}	102	0.924 4
	栎树 Quercus spp.	Y₁ = 0.719 3X₁^{1.029 6}	210	0.972 3	Y₂ = 0.495 5X₂^{0.869 8}	72	0.936 6
	桦树 Betula spp.	Y₁ = 0.855 1X₁^{0.979 1}	240	0.969 1	Y₂ = 0.335 9X₂^{0.941 4}	79	0.961 1
	人工杨 Populus simonii	Y₁ = 0.611 6X₁^{1.001 6}	150	0.990 4	Y₂ = 0.304 2X₂^{0.931 4}	48	0.990 1
	山杨 Populus davidiana	Y₁ = 0.631 0X₁^{0.998 7}	150	0.988 5	Y₂ = 0.281 6X₂^{0.951 6}	55	0.974 9
WS	云杉 Picea asperata	Y₁ = 0.818 1X₁^{0.927 3}	302	0.967 0	Y₂ = 0.211 5X₂^{1.009 8}	98	0.961 5
WS	冷杉 Abies fabri	Y₁ = 0.690 1X₁^{0.939 9}	301	0.985 5	Y₂ = 0.282 5X₂^{0.948 3}	101	0.950 8
XZ	云杉 Picea asperata	Y₁ = 0.943 8X₁^{0.919 1}	149	0.961 7	Y₂ = 0.196 3X₂^{0.983 1}	47	0.960 4
XZ	冷杉 Abies fabri	Y₁ = 0.607 3X₁^{0.950 6}	150	0.986 2	Y₂ = 0.190 3X₂^{1.033 0}	49	0.979 7
WS、XZ	落叶松 Larix dahurica	Y₁ = 0.716 8X₁^{0.929 3}	152	0.982 4	Y₂ = 0.190 1X₂^{1.006 6}	49	0.946 2
	栎树 Quercus spp.	Y₁ = 1.086 4X₁^{0.935 8}	151	0.980 0	Y₂ = 0.372 5X₂^{0.883 9}	50	0.953 8
	桦树 Betula spp.	Y₁ = 0.692 6X₁^{0.987 1}	150	0.977 6	Y₂ = 0.261 7X₂^{0.978 3}	53	0.944 6
	云南松 Pinus yunnanensis	Y₁ = 0.536 0X₁^{0.993 8}	150	0.986 7	Y₂ = 0.155 3X₂^{1.007 7}	50	0.973 1
	山杨 Populus davidiana	Y₁ = 0.642 3X₁^{0.977 2}	150	0.994 1	Y₂ = 0.275 0X₂^{0.912 3}	50	0.974 5
	思茅松 Pinus kesiya var. langbianensis	Y₁ = 0.391 8X₁^{1.060 3}	150	0.994 7	Y₂ = 0.170 1X₂^{0.984 2}	49	0.986 4
	高山松 Pinus densata	Y₁ = 0.786 5X₁^{0.958 5}	150	0.982 6	Y₂ = 0.156 2X₂^{1.030 6}	49	0.934 9
	柏木 Cupressus funebris	Y₁ = 1.020 3X₁^{0.931 2}	150	0.991 7	Y₂ = 0.232 6X₂^{0.936 4}	51	0.973 0
MS、ES	湿地松 Pinus elliottii	Y₁ = 0.677 4X₁^{0.980 1}	154	0.991 9	Y₂ = 0.388 9X₂^{0.917 3}	50	0.937 2
	柏木 Cupressus funebris	Y₁ = 0.949 6X₁^{0.950 4}	160	0.985 6	Y₂ = 0.216 7X₂^{1.011 0}	65	0.973 0
	栎树 Quercus spp.	Y₁ = 1.228 2X₁^{0.934 1}	149	0.982 8	Y₂ = 0.324 2X₂^{0.921 9}	53	0.905 9
	木荷 Schima superba	Y₁ = 0.857 3X₁^{0.975 3}	150	0.993 7	Y₂ = 0.294 0X₂^{0.992 0}	50	0.959 0
	枫香 Liquidambar formosana	Y₁ = 0.793 6X₁^{0.993 1}	152	0.991 0	Y₂ = 0.463 2X₂^{0.933 9}	50	0.966 6
	人工杨 Populus simonii	Y₁ = 0.545 8X₁^{1.019 9}	151	0.995 3	Y₂ = 0.221 9X₂^{0.933 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；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)，X₁为单木材积(m³)；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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表 2 全国各区域按森林类型建立的材积与生物量回归模型

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(组) 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
适用范围 Scope of application	建模树种(组) Modeling tree species (group)	模型表达式 Model expression	N	R²	模型表达式 Model expression	N	R²
NE	A	Y₁ = 0.683 9X₁^{0.965 7}	600	0.987 5	Y₂ = 0.257 9X₂^{1.035 3}	199	0.938 9
	B	Y₁ = 1.368 1X₁^{0.946 0}	1 060	0.943 9	Y₂ = 0.468 9X₂^{0.949 0}	361	0.882 7
	C	Y₁ = 1.114 3X₁^{0.941 8}	1 660	0.940 7	Y₂ = 0.382 1X₂^{0.977 9}	560	0.898 6
NN	A	Y₁ = 0.995 5X₁^{0.935 5}	449	0.970 8	Y₂ = 0.277 2X₂^{0.963 3}	150	0.952 9
	B	Y₁ = 0.745 0X₁^{1.001 2}	600	0.972 7	Y₂ = 0.373 0X₂^{0.941 9}	199	0.957 0
	C	Y₁ = 0.843 7X₁^{0.974 0}	1 049	0.970 9	Y₂ = 0.328 2X₂^{0.934 9}	349	0.954 2
NW	A	Y₁ = 0.880 3X₁^{0.920 6}	600	0.974 1	Y₂ = 0.293 8X₂^{0.960 6}	201	0.936 7
	B	Y₁ = 0.752 1X₁^{1.000 1}	600	0.972 4	Y₂ = 0.364 1X₂^{0.919 9}	206	0.953 3
	C	Y₁ = 0.821 5X₁^{0.957 1}	1 200	0.970 0	Y₂ = 0.329 5X₂^{0.938 3}	407	0.944 8
MS	A	Y₁ = 0.853 9X₁^{0.936 9}	433	0.982 2	Y₂ = 0.223 8X₂^{1.002 0}	149	0.956 2
	B	Y₁ = 0.829 7X₁^{0.977 4}	320	0.978 3	Y₂ = 0.229 2X₂^{0.919 7}	109	0.924 3
	C	Y₁ = 0.841 6X₁^{0.954 8}	753	0.979 0	Y₂ = 0.253 0X₂^{0.965 6}	258	0.941 8
ES	A	Y₁ = 0.737 4X₁^{0.951 1}	774	0.981 5	Y₂ = 0.220 5X₂^{0.998 8}	255	0.956 7
	B	Y₁ = 0.970 3X₁^{0.964 2}	341	0.985 2	Y₂ = 0.318 4X₂^{0.955 5}	115	0.940 4
	C	Y₁ = 0.800 6X₁^{0.955 6}	1 115	0.977 8	Y₂ = 0.245 3X₂^{0.987 4}	370	0.949 7
WS	A	Y₁ = 0.712 8X₁^{0.945 0}	1 337	0.978 2	Y₂ = 0.199 5X₂^{1.004 4}	446	0.959 0
	B	Y₁ = 0.803 0X₁^{0.968 0}	501	0.980 0	Y₂ = 0.310 7X₂^{0.931 7}	171	0.944 9
	C	Y₁ = 0.738 3X₁^{0.950 5}	1 838	0.976 6	Y₂ = 0.224 0X₂^{0.985 5}	617	0.953 3
XZ	A	Y₁ = 0.759 8X₁^{0.946 6}	569	0.971 8	Y₂ = 0.185 4X₂^{0.990 4}	186	0.950 6
	B	Y₁ = 0.642 3X₁^{0.977 2}	150	0.994 1	Y₂ = 0.275 0X₂^{0.912 3}	50	0.974 5
	C	Y₁ = 0.734 0X₁^{0.953 0}	719	0.976 4	Y₂ = 0.204 0X₂^{0.971 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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表 3 各区域各森林类型的生物量转换因子（BEF）和根茎比（RSR）比较

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	样本数 Sample number	平均值 Average value	最小值 Min. value	最大值 Max. value	标准差 SD	变动系数 Coefficient of variation/%
NE	A	BEF/(g·cm⁻³)	600	0.614	0.176	1.510	0.169	27.6
	A	RSR	199	0.354	0.079	2.581	0.289	81.8
	B	BEF/(g·cm⁻³)	1 060	0.675	0.040	3.561	0.215	31.9
	B	RSR	361	0.574	0.074	3.587	0.471	82.1
	C	BEF/(g·cm⁻³)	1 660	0.653	0.040	3.561	0.202	31.0
	C	RSR	560	0.496	0.074	3.587	0.429	86.5
NN	A	BEF/(g·cm⁻³)	449	0.834	0.295	3.041	0.322	38.6
	A	RSR	150	0.267	0.059	0.960	0.126	47.2
	B	BEF/(g·cm⁻³)	600	0.795	0.139	2.087	0.282	35.4
	B	RSR	199	0.303	0.036	1.200	0.162	53.5
	C	BEF/(g·cm⁻³)	1 049	0.812	0.139	3.041	0.300	37.0
	C	RSR	349	0.288	0.036	1.200	0.149	51.6
NW	A	BEF/(g·cm⁻³)	600	0.681	0.165	3.311	0.300	44.1
	A	RSR	201	0.287	0.052	1.351	0.154	53.6
	B	BEF/(g·cm⁻³)	600	0.799	0.139	2.087	0.282	35.3
	B	RSR	206	0.302	0.036	1.200	0.163	53.9
	C	BEF/(g·cm⁻³)	1 200	0.740	0.139	3.311	0.297	40.1
	C	RSR	407	0.295	0.036	1.351	0.158	53.8
MS	A	BEF/(g·cm⁻³)	433	0.699	0.200	6.236	0.338	48.4
	A	RSR	149	0.254	0.073	1.347	0.164	64.5
	B	BEF/(g·cm⁻³)	320	0.804	0.389	2.287	0.310	38.6
	B	RSR	109	0.430	0.033	1.301	0.247	57.4
	C	BEF/(g·cm⁻³)	753	0.744	0.200	6.236	0.330	44.4
	C	RSR	258	0.329	0.033	1.347	0.221	67.2
ES	A	BEF/(g·cm⁻³)	774	0.637	0.242	6.236	0.279	43.7
	A	RSR	255	0.243	0.065	0.838	0.120	49.1
	B	BEF/(g·cm⁻³)	341	0.874	0.396	2.287	0.279	31.9
	B	RSR	115	0.308	0.033	1.200	0.181	58.6
	C	BEF/(g·cm⁻³)	1 115	0.710	0.242	6.236	0.299	42.2
	C	RSR	370	0.264	0.033	1.200	0.144	54.7
WS	A	BEF/(g·cm⁻³)	1 337	0.603	0.134	2.428	0.227	37.6
	A	RSR	446	0.225	0.059	0.912	0.115	51.1
	B	BEF/(g·cm⁻³)	501	0.741	0.202	2.118	0.251	33.9
	B	RSR	171	0.273	0.020	0.954	0.141	51.6
	C	BEF/(g·cm⁻³)	1838	0.641	0.134	2.428	0.242	37.8
	C	RSR	617	0.238	0.020	0.954	0.125	52.3
XZ	A	BEF/(g·cm⁻³)	569	0.656	0.213	1.972	0.276	42.1
	A	RSR	186	0.199	0.045	0.559	0.093	47.0
	B	BEF/(g·cm⁻³)	150	0.593	0.295	1.309	0.114	19.2
	B	RSR	50	0.217	0.113	0.527	0.099	45.6
	C	BEF/(g·cm⁻³)	719	0.643	0.213	1.972	0.253	39.3
	C	RSR	236	0.203	0.045	0.559	0.095	46.8

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表 4 1949—2018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

调查期 Investigating period	林分 Stand				人工林 Plantation				天然林 Natural forest
调查期 Investigating period	FA	FV	FC	AC	FA	FV	FC	AC	FC	FV	FC	AC
1949	94.23	92.23	4.38	—	—	—	—	—	—	—	—	—
1950—1962	95.85	83.67	3.98	−0.033	—	—	—	—	—	—	—	—
1973—1976	119.78	84.70	3.79	−0.014	17.81	1.64	0.07		101.97	83.06	3.72
1977—1981	95.63	79.79	3.69	−0.020	12.73	2.73	0.13	0.011	82.90	77.06	3.56	−0.031
1984—1988	102.19	80.91	3.71	0.003	18.74	5.30	0.24	0.017	83.45	75.61	3.47	−0.014
1989—1993	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—1998	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—2003	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—2008	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—2013	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—2018	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—1962年两期资源数据不含西藏自治区的数据，1977—1981、1984—1988、1989—1993、1994—1998年4期数据统计不含西藏控制以外；FA为森林面积(10⁶ hm²)，FV为森林蓄积(10⁸ m³)，FC为碳储量(10¹² kg)，AC为年均碳累积(10¹² kg/a)；—表示没有调查统计数据。下同。Notes: The resource data for the periods of year 1949 and 1950−1962 do not include Tibet’s data, and data statistics for the periods of year 1977−1981, 1984−1988, 1989−1993 and 1994−1998 do not include data outside of Tibetan control; FA, forest area (10⁶ ha); FV, forest volume (10⁸ m³); FC, carbon storage (10¹² kg); AC, annual average carbon sequestration (10¹² kg/year); — indicates no survey statistic data. The same below.

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表 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—1962	1973—1976	1977—1981	1984—1988	1989—1993	1994—1998	1999—2003	2004—2008	2009—2013	2014—2018
NE	SF	0.97	5.91	6.20	7.48	9.49	10.59	10.55	10.20	6.51	6.15	6.93
NE	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
NN	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
NW	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
MS	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
ES	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
WS	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	—	—	0.00	6.27	0.00	2.70	4.30	1.26	1.19	1.13	0.94
XZ	FL	—	—	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
CH	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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表 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—1962	1973—1976	1977—1981	1984—1988	1989—1993	1994—1998	1999—2003	2004—2008	2009—2013	2014—2018
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	—	—	76.05	58.89	58.89	96.75	95.97	90.88	92.10	91.87	88.65

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表 7 本文碳储量与其他研究结果的对比

Table 7 Comparison of carbon storage results between this study and other research 10¹² kg

调查期 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]		朱永杰^[39] Zhu Y J^[39]	李妍等^[41] Li Y, et al.^[41]
调查期 Investigating period	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	—	—	—	—	—	—
1950—1962	3.98	4.35	4.58	—	—	—	—	—	—
1973—1976	3.79	4.32	4.44	—	—	4.11	4.38	—	3.85
1977—1981	3.69	4.30	4.38	4.30	4.72	4.21	4.75	4.09	3.70
1984—1988	3.71	4.38	4.45	4.46	4.89	4.18	4.82	4.04	3.76
1989—1993	4.08	4.87	4.63	4.93	5.40	4.52	5.25	4.76	4.11
1994—1998	4.56	5.30	4.75	5.01	5.39	4.50	5.12	5.25	4.66
1999—2003	5.43	6.15	—	5.85	5.86	5.41	5.97	6.49	5.51
2004—2008	6.10	6.68	—	—	6.43	6.24	6.83	7.895	6.09
2009—2013	6.81	7.45	—	—	—	—	—	—	—
2014—2018	7.97	8.60	—	—	—	—	—	—	—

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1949—2018年中国森林资源碳储量变化研究

作者简介: 张煜星，博士，教授级高级工程师。主要研究方向：森林资源监测和森林碳汇。Email：mrqzyx@sina.com 地址：100714北京市东城区朝阳门内大街130号国家林业和草原局林产工业规划设计院

责任作者: 王雪军，博士，教授级高级工程师。主要研究方向：森林资源监测与评价。Email：wangxuejun320@126.com 地址：100714北京市东城区和平里东街18号国家林业和草原局森林资源管理司

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Changes in forest resource carbon storage in China between 1949 and 2018

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作者简介:
张煜星，博士，教授级高级工程师。主要研究方向：森林资源监测和森林碳汇。Email：mrqzyx@sina.com　地址：100714北京市东城区朝阳门内大街130号国家林业和草原局林产工业规划设计院

责任作者:
王雪军，博士，教授级高级工程师。主要研究方向：森林资源监测与评价。Email：wangxuejun320@126.com　地址：100714北京市东城区和平里东街18号国家林业和草原局森林资源管理司