东北六种温带森林碳密度和固碳能力
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摘要
森林生态系统吸收大气中CO2并固定在植被和土壤中,因而在减少日益增长的温室效应和维持气候系统的稳定中起到至关重要的作用。精确估算森林碳储量和碳通量是评价森林生态系统对全球碳收支贡献的首要条件,而探索森林碳分配格局及其影响因子对于构建陆地生态系统模型和评价预测森林碳循环对全球变化的响应也非常重要。本研究以处于同一气候区内林龄相近的六种温带森林(即杨桦林、硬阔叶林、红松林、兴安落叶松林、杂木林和蒙古栎林)为研究对象,旨在量化六种林型十种主要组成树种的碳浓度变异以及采用不同碳浓度估算生物量碳的误差,同时采用样地清查和异速生长方程法量化六种林型的碳密度和净初级生产力(NPP)的分配格局及其控制因子,并评价其固碳能力。主要研究结果如下：
十种主要树种生物量器官的平均碳浓度波动在47.1%(细根)至51.4%(叶)之间,其中树干总平均碳浓度为49.9±1.3%(平均值±标准误)。质量加权平均碳浓度(weighted mean carbon concentration,WMCC)的大小顺序为：黄菠萝(Phellodendron amurense Rupr.)(55.1%)>紫椴(Tilia amurensis Rupr.)(53.9%)>红松(Pinus koraiensis Sieb.et Zucc.)(53.2%)>水曲柳(Fraxinus mandshurica Rupr.)(52.9%)>胡桃楸(Juglans mandshurica Maxim.)(52.4%)>蒙古栎(Quercus mongolica Fisch.)(47.6%)>兴安落叶松(Larix gmelinii Rupr.)(46.9%)>五角槭(Acer mono Maxim.)(46.4%)>白桦(Betula platyphylla Suk.)(46.1％)>山杨(Populous davidians Dode)(43.7%)。忽略上述碳浓度的种内和种间变异将引起的生物碳储量估算误差波动在-6.7%至+7.2%之间,其中约93%的误差是因碳浓度在种内不同生物量器官间的变异引起的。WMCC与优势木的平均年增长量呈显著负相关关系,表明在固碳林营造时选择速生树种的同时,应该折中考虑其较低碳浓度而引起的固碳量损失。
林龄相近的六种林型,虽然所处的立地条件和林分组成不同,但林型间的生态系统碳密度及其组分(除碎屑碳库外)差异不显著,而利用胸高断面积标准化之后却发现其差异显著。六种林型的总碳密度波动在186.9-349.1 tC hm-2之间；其中,植被碳密度、碎屑碳密度、土壤碳密度分别波动在86.3-122.7、6.5-10.5、93.7-220.1 tC hm-2之间,分别占总碳密度的39.7%±7.1%(均值±标准差)、3.3%±1.1%、57.0%±7.9%。在植被碳库中,乔木层占99%以上。叶生物量、中细根(直径<5mm)生物量、根冠比、中细根与叶量之比分别波动在2.08-4.72 tC hm-2、0.95-3.24 tC hm-2、22.0-28.3％、34.5-122.2%之间。六种林型中,以红松林的叶生产效率(总生物量与叶量之比)最低(22.6 g g-1)、兴安落叶松林的中细根生产效率(总生物量与中细根生物量之比)最高(124.7 g g-1)。除蒙古栎林之外,所有林型的中细根碳密度均随土壤层次加深而下降；而蒙古栎林的中细根碳密度的垂直分布却有下移趋势。两种人工林(红松林和落叶松林)的粗木质残体碳密度显著地低于天然林。这些结果表明,特定森林的碳分配格局分异主要受控于植被功能型、经营历史、局域土壤的水分和养分有效性等的共同作用。
六种林型的总NPP波动在615.9-860.4 gC m-2a-1之间,平均值为763.2 gC m-2a-1。由于立地条件和组成植被功能型的不同,总NPP的林型间差异显著,其中NPP林型间的分异主要来源于地下NPP,而地上NPP差异不显著。另外,短期存活组织(即资源获取组织)NPP也存在显著的差异。除兴安落叶松林外,其余五种林型在地上和地下NPP、长期存活组织和短期存活组织NPP的分配格局基本一致,均以地上NPP(占总NPP的1/2以上)和短期存活组织NPP(占总NPP的2/3以上)为主。六种林型净生态系统生产力(NEP)波动在301.9-729.2 gC m-2a-1,均表现出较强的碳汇功能。
本论文对我国东北典型温带森林碳密度和碳汇功能进行了系统的研究,为区域森林碳循环模型的构建和校验提供了重要的实测数据,也为东北地区碳汇林业提供了科学依据。
Forest ecosystem plays a key role in reducing the ongoing enhanced greenhouse effect and stabilizing the climatic system by sequestering the atmospheric CO2 into vegetation and soils. Quantifying forest carbon (C) storage and flux accurately is prerequisite to assess the contribution of forest ecosystem to the global carbon budget. Exploring forest C distribution and its influencing factors is also enssential to developing terrestrial ecosystem models and predicting responses of forest C cycling to global changes. In this study, we investigated six representative temperate forests with similar stand age (42-59 years old) and under same climate conditions in northeastern China. The forests were aspen-birch forest, hardwood forest, Korean pine plantation, Dahurian larch plantation, mixed deciduous forest, and Mongolian oak forest. The aims of this study were to:(1) examine inter-and intra-specific variations of C concentration ([C]) in biomass tissues for 10 co-occurring temperate tree species in the forests; and (2) measure C density, net primary production (NPP) and their distribution patterns so as to assess C sequestration capacity of the forests with forest inventory and allometry approaches. The main results were as follows:
The mean biomass tissue [C] across the ten species varied from 47.1% in fine root to 51.4% in foliage. The mean stem [C] of the species was 49.9±1.3%(mean±SE). The weighted mean C concentration (WMCC) for the species ranked as:Amur cork-tree (Phellodendron amurense Rupr.) (55.1%)> Amur linden (Tilia amurensis Rupr.) (53.9%)> Korean pine (Pinus koraiensis Sieb. et Zucc.) (53.2%)> Manchurian ash (Fraxinus mandshurica Rupr.) (52.9%)> Manchurian walnut (Juglans mandshurica Maxim.) (52.4%)> Mongolian oak (Quercus mongolica Fisch.) (47.6%)> Dahurian larch (Larix gmelinii Rupr.) (46.9%)> Mono maple (Acer mono Maxim.) (46.4%)> white birch (Betula platyphylla Suk.) (46.1%)> aspen (Populous davidiana Dode)(43.7%) (43.7%). Failing to account for the inter-and intra-specific variations in [C] will introduce a relative error of-6.7% to+7.2% in estimates of biomass C stock from inventory data, of which 93% is attributed to ignoring the inter-specific variation in [C]. The WMCC of the dominant trees was negatively correlated to mean annual increment of biomass (MAI), suggesting that planting fast-growing tree species for C sequestration in afforestation and reforestation practices sacrifice some C gain from increasing MAI due to decreasing [C].
There were no significant differences in the C densities of ecosystem components (except for detritus) although the six forests had various vegetation compositions under divergent site conditions. The differences, however, were significant when the C pools were normalized with stand basal area. The total ecosystem C density varied from 186.9 tC hm-2to 349.1 tC hm-2 across the forests. The C densities of vegetation, detritus, and soil ranged 86.3-122.7 tC hm-2, 6.5-10.5 tC hm-2, and 93.7-220.1 tC hm-2, respectively, which accounted for 39.7%±7.1% (mean±SD),3.3%±1.1%, and 57.0%±7.9% of the total C density, respectively. The overstory C pool accounted for>99% of the vegetation C pool. The foliage biomass, small root (diameter<5mm) biomass, root-shoot ratio, and small root to foliage biomass ratio varied from 2.08-4.72 tC hm-2,0.95-3.24 tC hm-2,22.0-28.3%, and 34.5-122.2%, respectively. The Korean pine plantation had the lowest foliage productive efficiency (total biomass/foliage biomass:22.6 g g-1) among the six forests, while the Dahurian larch plantation had the highest small root production efficiency (total biomass/small root biomass:124.7 g g-1). The small root C density decreased with soil depths for all forests except for the Mongolian oak forest, in which the small roots tended to be vertically distributed downwards. The C density of coarse woody debris was significantly less in the two plantations than in the four naturally regenerated forests. This study illustrates that the variability of C allocation patterns in a specified forest is jointly influenced by vegetation type, management history, local water and nutrient availability; it also provides important data for developing and validating carbon cycling models for temperate forests.
The total NPP (TNPP) of the six forests varied from 615.9 to 860.4 gC m-2a-1, averaging 763.2 gC m-2a-1.There were no significant differences in the aboveground NPP (ANPP) among the six forests, although the forests had various vegetation compositions under divergent site conditions. However, the TNPP differed significantly among the forests, mainly attributed to the difference in the belowground NPP (BNPP). Additionally, the NPP of short-living tissues (NPPSL) (i.e., the tissues that assimilated resource) differed significantly. The allocation patterns of TNPP to BNPP or NPPSL were similar across the six forests except for the Dahurian larch plantation. More than one half and two thirds of TNPP was allocated to ANPP and NPPSL, respectively. The six forests had strongly carbon sequestration potential, The net ecosystem production (NEP) varied from 301.9 to 729.2 gC m-2a-1 across the six forests, suggesting the forests as strong C sinks.
This comprehensive investigation on forest C density and sink strength provides important data for developing and validating C cycling models for the temperate forests, and scientific basis for forest C sequestration management in this region.
十种主要树种生物量器官的平均碳浓度波动在47.1%(细根)至51.4%(叶)之间,其中树干总平均碳浓度为49.9±1.3%(平均值±标准误)。质量加权平均碳浓度(weighted mean carbon concentration,WMCC)的大小顺序为：黄菠萝(Phellodendron amurense Rupr.)(55.1%)>紫椴(Tilia amurensis Rupr.)(53.9%)>红松(Pinus koraiensis Sieb.et Zucc.)(53.2%)>水曲柳(Fraxinus mandshurica Rupr.)(52.9%)>胡桃楸(Juglans mandshurica Maxim.)(52.4%)>蒙古栎(Quercus mongolica Fisch.)(47.6%)>兴安落叶松(Larix gmelinii Rupr.)(46.9%)>五角槭(Acer mono Maxim.)(46.4%)>白桦(Betula platyphylla Suk.)(46.1％)>山杨(Populous davidians Dode)(43.7%)。忽略上述碳浓度的种内和种间变异将引起的生物碳储量估算误差波动在-6.7%至+7.2%之间,其中约93%的误差是因碳浓度在种内不同生物量器官间的变异引起的。WMCC与优势木的平均年增长量呈显著负相关关系,表明在固碳林营造时选择速生树种的同时,应该折中考虑其较低碳浓度而引起的固碳量损失。
林龄相近的六种林型,虽然所处的立地条件和林分组成不同,但林型间的生态系统碳密度及其组分(除碎屑碳库外)差异不显著,而利用胸高断面积标准化之后却发现其差异显著。六种林型的总碳密度波动在186.9-349.1 tC hm-2之间；其中,植被碳密度、碎屑碳密度、土壤碳密度分别波动在86.3-122.7、6.5-10.5、93.7-220.1 tC hm-2之间,分别占总碳密度的39.7%±7.1%(均值±标准差)、3.3%±1.1%、57.0%±7.9%。在植被碳库中,乔木层占99%以上。叶生物量、中细根(直径<5mm)生物量、根冠比、中细根与叶量之比分别波动在2.08-4.72 tC hm-2、0.95-3.24 tC hm-2、22.0-28.3％、34.5-122.2%之间。六种林型中,以红松林的叶生产效率(总生物量与叶量之比)最低(22.6 g g-1)、兴安落叶松林的中细根生产效率(总生物量与中细根生物量之比)最高(124.7 g g-1)。除蒙古栎林之外,所有林型的中细根碳密度均随土壤层次加深而下降；而蒙古栎林的中细根碳密度的垂直分布却有下移趋势。两种人工林(红松林和落叶松林)的粗木质残体碳密度显著地低于天然林。这些结果表明,特定森林的碳分配格局分异主要受控于植被功能型、经营历史、局域土壤的水分和养分有效性等的共同作用。
六种林型的总NPP波动在615.9-860.4 gC m-2a-1之间,平均值为763.2 gC m-2a-1。由于立地条件和组成植被功能型的不同,总NPP的林型间差异显著,其中NPP林型间的分异主要来源于地下NPP,而地上NPP差异不显著。另外,短期存活组织(即资源获取组织)NPP也存在显著的差异。除兴安落叶松林外,其余五种林型在地上和地下NPP、长期存活组织和短期存活组织NPP的分配格局基本一致,均以地上NPP(占总NPP的1/2以上)和短期存活组织NPP(占总NPP的2/3以上)为主。六种林型净生态系统生产力(NEP)波动在301.9-729.2 gC m-2a-1,均表现出较强的碳汇功能。
本论文对我国东北典型温带森林碳密度和碳汇功能进行了系统的研究,为区域森林碳循环模型的构建和校验提供了重要的实测数据,也为东北地区碳汇林业提供了科学依据。
Forest ecosystem plays a key role in reducing the ongoing enhanced greenhouse effect and stabilizing the climatic system by sequestering the atmospheric CO2 into vegetation and soils. Quantifying forest carbon (C) storage and flux accurately is prerequisite to assess the contribution of forest ecosystem to the global carbon budget. Exploring forest C distribution and its influencing factors is also enssential to developing terrestrial ecosystem models and predicting responses of forest C cycling to global changes. In this study, we investigated six representative temperate forests with similar stand age (42-59 years old) and under same climate conditions in northeastern China. The forests were aspen-birch forest, hardwood forest, Korean pine plantation, Dahurian larch plantation, mixed deciduous forest, and Mongolian oak forest. The aims of this study were to:(1) examine inter-and intra-specific variations of C concentration ([C]) in biomass tissues for 10 co-occurring temperate tree species in the forests; and (2) measure C density, net primary production (NPP) and their distribution patterns so as to assess C sequestration capacity of the forests with forest inventory and allometry approaches. The main results were as follows:
The mean biomass tissue [C] across the ten species varied from 47.1% in fine root to 51.4% in foliage. The mean stem [C] of the species was 49.9±1.3%(mean±SE). The weighted mean C concentration (WMCC) for the species ranked as:Amur cork-tree (Phellodendron amurense Rupr.) (55.1%)> Amur linden (Tilia amurensis Rupr.) (53.9%)> Korean pine (Pinus koraiensis Sieb. et Zucc.) (53.2%)> Manchurian ash (Fraxinus mandshurica Rupr.) (52.9%)> Manchurian walnut (Juglans mandshurica Maxim.) (52.4%)> Mongolian oak (Quercus mongolica Fisch.) (47.6%)> Dahurian larch (Larix gmelinii Rupr.) (46.9%)> Mono maple (Acer mono Maxim.) (46.4%)> white birch (Betula platyphylla Suk.) (46.1%)> aspen (Populous davidiana Dode)(43.7%) (43.7%). Failing to account for the inter-and intra-specific variations in [C] will introduce a relative error of-6.7% to+7.2% in estimates of biomass C stock from inventory data, of which 93% is attributed to ignoring the inter-specific variation in [C]. The WMCC of the dominant trees was negatively correlated to mean annual increment of biomass (MAI), suggesting that planting fast-growing tree species for C sequestration in afforestation and reforestation practices sacrifice some C gain from increasing MAI due to decreasing [C].
There were no significant differences in the C densities of ecosystem components (except for detritus) although the six forests had various vegetation compositions under divergent site conditions. The differences, however, were significant when the C pools were normalized with stand basal area. The total ecosystem C density varied from 186.9 tC hm-2to 349.1 tC hm-2 across the forests. The C densities of vegetation, detritus, and soil ranged 86.3-122.7 tC hm-2, 6.5-10.5 tC hm-2, and 93.7-220.1 tC hm-2, respectively, which accounted for 39.7%±7.1% (mean±SD),3.3%±1.1%, and 57.0%±7.9% of the total C density, respectively. The overstory C pool accounted for>99% of the vegetation C pool. The foliage biomass, small root (diameter<5mm) biomass, root-shoot ratio, and small root to foliage biomass ratio varied from 2.08-4.72 tC hm-2,0.95-3.24 tC hm-2,22.0-28.3%, and 34.5-122.2%, respectively. The Korean pine plantation had the lowest foliage productive efficiency (total biomass/foliage biomass:22.6 g g-1) among the six forests, while the Dahurian larch plantation had the highest small root production efficiency (total biomass/small root biomass:124.7 g g-1). The small root C density decreased with soil depths for all forests except for the Mongolian oak forest, in which the small roots tended to be vertically distributed downwards. The C density of coarse woody debris was significantly less in the two plantations than in the four naturally regenerated forests. This study illustrates that the variability of C allocation patterns in a specified forest is jointly influenced by vegetation type, management history, local water and nutrient availability; it also provides important data for developing and validating carbon cycling models for temperate forests.
The total NPP (TNPP) of the six forests varied from 615.9 to 860.4 gC m-2a-1, averaging 763.2 gC m-2a-1.There were no significant differences in the aboveground NPP (ANPP) among the six forests, although the forests had various vegetation compositions under divergent site conditions. However, the TNPP differed significantly among the forests, mainly attributed to the difference in the belowground NPP (BNPP). Additionally, the NPP of short-living tissues (NPPSL) (i.e., the tissues that assimilated resource) differed significantly. The allocation patterns of TNPP to BNPP or NPPSL were similar across the six forests except for the Dahurian larch plantation. More than one half and two thirds of TNPP was allocated to ANPP and NPPSL, respectively. The six forests had strongly carbon sequestration potential, The net ecosystem production (NEP) varied from 301.9 to 729.2 gC m-2a-1 across the six forests, suggesting the forests as strong C sinks.
This comprehensive investigation on forest C density and sink strength provides important data for developing and validating C cycling models for the temperate forests, and scientific basis for forest C sequestration management in this region.
引文
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