基于年轮分析的不同恢复途径下森林乔木层生物量和蓄积量的动态变化

doi:10.3724/SP.J.1258.2012.00117

摘要/Abstract

摘要：

基于树木年轮学与标准地调查法, 研究了川西亚高山林区3种恢复森林类型生物量、蓄积量及生产力动态变化特征, 旨在尝试年轮学在森林生长过程反演中的运用, 并探索不同恢复模式下森林生物量和蓄积量的动态变化。结果表明, 不同恢复类型发育至20年以后, 均进入生长加速期, 平均胸径间差异逐渐显著, 人工云杉(Picea asperata)林胸径增长最快, 明显高于天然恢复的次生桦木(Betula spp.)林和次生针阔混交林。在恢复过程中, 次生针阔混交林一直保持最高的林分平均地上生物量与林分蓄积量, 其地上平均生物量一直显著高于人工云杉林(p < 0.05), 在20年以后显著高于次生桦木林(p < 0.05)。与人工云杉林相比, 次生桦木林在25年前具有相对较高的生物量, 而在25年之后则低于人工云杉林。在0-20年桦木林林分蓄积量略高于云杉林, 而20年以后, 云杉林蓄积量则超过桦木林。不同恢复类型的生产力大小对比显示, 30年之前, 次生针阔混交林>次生桦木林>人工云杉林, 30年之后, 针阔混交林生产力仍然最高, 而人工云杉林则超过次生桦木林。川西林区次生针阔混交林恢复模式在生物量和蓄积量积累方面均具有显著优势。

关键词: 生物量, 森林恢复, 净第一性生产力, 林分蓄积量, 年轮

Abstract:

Aims Our objectives were to (a) explore potential applications of tree-ring analysis for evaluating biomass dynamics of different forest restoration approaches in Western Sichuan, (b) compare aboveground biomass and stem volume with differently restored forests, and (c) identify the appropriate management approaches for different management aims.
Methods We intensively surveyed three replicated plots for each restoration approach and cored and measured all living trees with diameter at breast height (DBH) ≥ 5 cm using dendroecological methods. Dynamics of aboveground biomass and stem volume were calculated by means of allometric relationships and one-way tree volume models based on continuous variation of DBH.
Important findings Forests in all three restoration approaches entered into an accelerated growth phase after 20 years, when significant differences in average DBH were observed among different forest types. Planted spruce (Picea asperata) forest (PSF) showed faster growth in mean DBH than secondary birch (Betula spp.) forest (SBF) and secondary coniferous and broad-leaved mixed forest (SMF). In the process of recovery, SMF had the highest aboveground biomass and stand volume; its biomass was significant higher than that of PSF (p < 0.05) throughout and higher than SBF after 20 years. SBF had a higher aboveground biomass compared with that for PSF during 1-25 years and a lower value after 25 years. Before 20 years, the stand volume of SBF was higher than that of PSF, but PSF had higher volume after 20 years. Before 30 years, the aboveground net primary productivity for three forest types ranked SMF>SBF>PSF. After 30 years, the order changed to SMF>PSF>SBF. Results indicated that SMF had an advantage in both biomass and stand volume accumulation among the three restoration approaches.

Key words: biomass, forest restoration, net primary productivity (NPP), stand volume, tree ring

张远东, 刘彦春, 刘世荣, 张笑鹤. 基于年轮分析的不同恢复途径下森林乔木层生物量和蓄积量的动态变化. 植物生态学报, 2012, 36(2): 117-125. DOI: 10.3724/SP.J.1258.2012.00117

ZHANG Yuan-Dong, LIU Yan-Chun, LIU Shi-Rong, ZHANG Xiao-He. Dynamics of stand biomass and volume of the tree layer in forests with different restoration approaches based on tree-ring analysis. Chinese Journal of Plant Ecology, 2012, 36(2): 117-125. DOI: 10.3724/SP.J.1258.2012.00117

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https://www.plant-ecology.com/CN/Y2012/V36/I2/117

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参考文献 24

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森林类型 Forest type	海拔 Elevation (m)	坡向 Slope aspect (°)	坡度 Slope gradient (°)	林分密度 Stand density (tree · hm^-2)	平均胸径 Mean DBH (cm)	林龄 Stand age (a)	样芯数 No. of cores
PSFI	3 212	NE 40	10	829.3	21.4 ± 6.2	43	47
PSFII	3 261	NE 45	15	914.5	20.1 ± 5.7	44	49
PSFIII	3 252	SE 70	10	964.7	19.7 ± 5.6	39	53
SBFI	3 214	NW 40	26	3 021.5	9.3 ± 3.4	49	104
SBFII	3 238	NW 25	20	3 086.1	11.2 ± 3.3	45	77
SBFIII	3 326	NE 20	18	2 788.1	10.1 ± 4.5	50	94
SMFI	3 020	NE 40	30	3 262.0	11.1 ± 3.4	36	93
SMFII	2 990	NE 20	20	3 188.1	9.5 ± 3.4	35	124
SMFIII	3 345	NE 15	20	3 032.7	11.7 ± 4.6	38	101

森林类型 Forest type	海拔 Elevation (m)	坡向 Slope aspect (°)	坡度 Slope gradient (°)	林分密度 Stand density (tree · hm^-2)	平均胸径 Mean DBH (cm)	林龄 Stand age (a)	样芯数 No. of cores
PSFI	3 212	NE 40	10	829.3	21.4 ± 6.2	43	47
PSFII	3 261	NE 45	15	914.5	20.1 ± 5.7	44	49
PSFIII	3 252	SE 70	10	964.7	19.7 ± 5.6	39	53
SBFI	3 214	NW 40	26	3 021.5	9.3 ± 3.4	49	104
SBFII	3 238	NW 25	20	3 086.1	11.2 ± 3.3	45	77
SBFIII	3 326	NE 20	18	2 788.1	10.1 ± 4.5	50	94
SMFI	3 020	NE 40	30	3 262.0	11.1 ± 3.4	36	93
SMFII	2 990	NE 20	20	3 188.1	9.5 ± 3.4	35	124
SMFIII	3 345	NE 15	20	3 032.7	11.7 ± 4.6	38	101

树种 Tree species	地上部分器官 Aboveground organ		异速生长模型 Allometric model	决定系数 Determination coefficient	文献来源 Origin of references
冷杉 Abies spp.	干 Stem		W = 0.0139(D²H)^1.0075	R² = 0.998 6	Luo et al., 2002
	枝 Branch		W = 0.0014(D²H)^1.0503	R² = 0.911 8
	叶 Leaf	胸径 DBH < 40 cm时,	W = 0.0003(D²H)^1.2032	R² = 0.934 1
	叶 Leaf	胸径 DBH > 40 cm时,	W = 11.5060ln(D²H) - 74.7330	R² = 0.753 9
云杉 Picea spp.	干 Stem		W = 0.0405D^2.5680	R² = 0.989 0	Luo et al., 2002
	枝 Branch		W = 0.0037D^2.7386	R² = 0.945 0
	叶 Leaf	胸径 DBH < 40 cm时,	W = 0.0014D^2.9302	R² = 0.941 9
	叶 Leaf	胸径 DBH > 40 cm时,	W = 29.5410lnD - 63.1500	R² = 0.757 4
桦木 Betula spp.	干 Stem		W = 0.1411(D²H)^0.7234	R² = 0.980 1	Feng et al., 1999
	枝 Branch		W = 0.0072(D²H)^1.0225	R² = 0.774 4
	叶 Leaf		W = 0.0151(D²H)^0.8085	R² = 0.828 1
树种 Tree species	地上部分器官 Aboveground organ		异速生长模型 Allometric model	决定系数 Determination coefficient	文献来源 Origin of references
槭树 Acer spp.	干 Stem		W = 0.3274(D²H)^0.7218	R² = 0.932 5	Chen, 1983
	枝 Branch		W = 0.0135(D²H)^0.7198	R² = 0.911 4
	叶 Leaf		W = 0.0235(D²H)^0.6929	R² = 0.891 7
杨木 Poplar spp.	干 Stem		W = 0.0537(D²H)^0.9270	R² = 0.987 0	Zhu et al., 1988
	枝 Branch		W = 0.0125(D²H)^0.9504	R² = 0.863 0
	叶 Leaf		W = 0.0221(D²H)^0.7583	R² = 0.786 0
其他阔叶树 Other broadleaf species	干 Stem		W = 0.0097(D²H) + 5.8252	R² = 0.991 4	Luo et al., 2002
	枝 Branch		W = 0.0510(D²H) + 3.5080	R² = 0.982 5
	叶 Leaf		W = 0.0004(D²H) + 0.7563	R² = 0.933 3

树种 Tree species	地上部分器官 Aboveground organ		异速生长模型 Allometric model	决定系数 Determination coefficient	文献来源 Origin of references
冷杉 Abies spp.	干 Stem		W = 0.0139(D²H)^1.0075	R² = 0.998 6	Luo et al., 2002
	枝 Branch		W = 0.0014(D²H)^1.0503	R² = 0.911 8
	叶 Leaf	胸径 DBH < 40 cm时,	W = 0.0003(D²H)^1.2032	R² = 0.934 1
	叶 Leaf	胸径 DBH > 40 cm时,	W = 11.5060ln(D²H) - 74.7330	R² = 0.753 9
云杉 Picea spp.	干 Stem		W = 0.0405D^2.5680	R² = 0.989 0	Luo et al., 2002
	枝 Branch		W = 0.0037D^2.7386	R² = 0.945 0
	叶 Leaf	胸径 DBH < 40 cm时,	W = 0.0014D^2.9302	R² = 0.941 9
	叶 Leaf	胸径 DBH > 40 cm时,	W = 29.5410lnD - 63.1500	R² = 0.757 4
桦木 Betula spp.	干 Stem		W = 0.1411(D²H)^0.7234	R² = 0.980 1	Feng et al., 1999
	枝 Branch		W = 0.0072(D²H)^1.0225	R² = 0.774 4
	叶 Leaf		W = 0.0151(D²H)^0.8085	R² = 0.828 1
树种 Tree species	地上部分器官 Aboveground organ		异速生长模型 Allometric model	决定系数 Determination coefficient	文献来源 Origin of references
槭树 Acer spp.	干 Stem		W = 0.3274(D²H)^0.7218	R² = 0.932 5	Chen, 1983
	枝 Branch		W = 0.0135(D²H)^0.7198	R² = 0.911 4
	叶 Leaf		W = 0.0235(D²H)^0.6929	R² = 0.891 7
杨木 Poplar spp.	干 Stem		W = 0.0537(D²H)^0.9270	R² = 0.987 0	Zhu et al., 1988
	枝 Branch		W = 0.0125(D²H)^0.9504	R² = 0.863 0
	叶 Leaf		W = 0.0221(D²H)^0.7583	R² = 0.786 0
其他阔叶树 Other broadleaf species	干 Stem		W = 0.0097(D²H) + 5.8252	R² = 0.991 4	Luo et al., 2002
	枝 Branch		W = 0.0510(D²H) + 3.5080	R² = 0.982 5
	叶 Leaf		W = 0.0004(D²H) + 0.7563	R² = 0.933 3

树种 Tree species	材积公式 Volume equation (m³)
桦木 Betula spp.	$V = 0.00004894 \times {\left( {0.9839 \times D - 0.3303} \right)^{2.0173}} \times {\left( {\frac{{33.2727 - 1031.4484}}{{31.549 + D}}} \right)^{0.9388}}$
冷杉 Abies spp.	$V = 0.00006322 \times {\left( { - 0.1027 + 0.99576 \times D} \right)^{1.901}} \times {\left( {\frac{{45.79737 - 1837.226}}{{D + 38.40604}}} \right)^{0.963}}$
云杉 Picea spp.	$V = 0.00005679 \times {\left( {0.37388 + 0.9721 \times D} \right)^{1.852}} \times {\left( {\frac{D}{{1.129 + 0.0161 \times D}}} \right)^{1.0335}}$
杨树 Poplar spp.	$V = 0.00005275 \times {\left( { - 0.5162 + 1.0942 \times D} \right)^{1.94526}} \times {\left( {\frac{D}{{0.74623 + 0.0421 \times D}}} \right)^{0.93885}}$
槭树 Acer spp.	$V = 0.00005275 \times {\left( {0.49896 + 0.9661 \times D} \right)^{1.945}} \times {\left( {\frac{D}{{0.84118 + 0.0381}}} \right)^{0.93885}}$