浑善达克沙地榆树疏林和小叶杨人工林碳密度特征及其与林龄的关系

榆树(Ulmus pumila)疏林是浑善达克沙地的地带性隐域植被, 小叶杨(Populus simonii)是该区域主要的防风固沙造林树种。该文通过测定两种森林生态系统乔木层(叶、枝、干、根)、草本层(地上植被和地下根系)和土壤层(0-100 cm)的碳含量, 比较了两种森林生态系统的碳密度及其分配特征, 并运用空间代替时间的方法, 阐明了乔木层、土壤层和总碳密度随林龄增加的变化特征, 估算了两种森林生态系统的固碳速率。结果表明, 榆树疏林乔木层和土壤层平均碳含量都低于小叶杨人工林, 榆树疏林生态系统总碳密度是小叶杨人工林的1/2。两种森林生态系统的总碳密度中, 乔木层碳密度和土壤层碳密度总占比98%以上; 土壤层与植被层碳密度的比值随林龄的增加而降低, 过熟林时该比值分别为1.66 (榆树疏林)和1.87 (小叶杨人工林); 榆树疏林和小叶杨人工林的乔木层、土壤层和生态系统的总碳密度随林龄的增加而增加, 其中乔木层碳密度及榆树疏林总碳密度与林龄均呈现出显著的线性正相关关系。小叶杨人工林乔木层的固碳速率约为榆树疏林的5倍, 榆树疏林生态系统和小叶杨人工林生态系统的总固碳速率分别为0.81 Mg C·hm^-2·a^-1和5.35 Mg C·hm^-2·a^-1。这一研究结果有利于估算沙地森林生态系统的碳储量, 为区域生态环境恢复和增加碳汇的政策制定提供依据。     

Current stocks and rate of sequestration of forest carbon in Gansu Province,China

Aims
Carbon sequestration is the basic function and most primary service of forest ecosystems, and plays a vital role in mitigating the global climate change. However, carbon storage and allocation in forest ecosystems have been less studied at regional scales than at forest stand levels, and the results are subject to uncertainty due to inconsistent methodologies. In this study we aim to obtain relatively accurate estimates of forest carbon stocks and sequestration rate at a provincial scale (regional) based on plot surveys of plants and soils.
Methods
In consideration of the areas and distributions of major forest types, 212 sampling plots, covering different age classes and origins (natural forests vs. planted forests), were surveyed in Gansu Province in northern China. Field investigations were conducted for vegetation layers (trees, shrubs, herbs and litter), soil profiles, and sampling of both plant materials and soils for laboratory analyses. Regional carbon stocks were calculated by up-scaling the carbon densities of all forest types with their corresponding areas. Carbon sequestration rate was estimated by referencing the reports of national forest inventory data for different periods.
Important findings Forest carbon stocks at the provincial scale were estimated at 612.43 Tg C, including 179.04 Tg C in biomass and 433.39 Tg C in soil organic materials. Specifically, natural forests stored 501.42 Tg C, approximately 4.52 times than that of the plantations. Biomass carbon density in both natural forests and plantations showed an increasing trend with stand age classes, and was greater in natural forests than in plantations within the same age classes. Soil carbon density also increased with stand age classes in natural forests, but the highest value occurred at the pre-mature stage in plantations. The weighted average of regional biomass carbon density was at 72.43 Mg C·hm^-2, with the average value of 90.52 Mg C·hm^-2 in natural forests and 33.79 Mg C·hm^-2 in plantations, respectively. In 1996, vegetation stored 132.47 Tg C in natural forests and 12.81 Tg C in plantations, respectively, and the values increased to 152.41 and 26.63 Tg C in 2011, with the mean carbon sequestration rates of 1.33 and 0.92 Tg C·a^-1. Given that young and middle-aged forests account for a large proportion (62.28%) of the total forest areas, the region is expected to have substantial potential of carbon sequestration.     

Carbon storage and its distribution of forest ecosystems in Zhejiang Province,China

Aims
The concentration of CO₂ and other greenhouse gases in the atmosphere has considerably increased over last century and is set to rise further. Forest ecosystems play a key role in reducing CO₂ concentration in the atmosphere and mitigating global climate change. Our objective is to understand carbon storage and its distribution in forest ecosystems in Zhejiang Province, China.
Methods
By using the 8th forest resource inventory data and 2011-2012 field investigation data, we estimated carbon storage, density and its distribution in forest ecosystems of Zhejiang Province.
Important findings
The carbon storage of forest ecosystems in Zhejiang Province was 602.73 Tg, of which 122.88 Tg in tree layer, 16.73 Tg in shrub-herb layer, 11.36 Tg in litter layer and 451.76 Tg in soil layer accounting for 20.39%, 2.78%, 1.88% and 74.95% of the total carbon storage, respectively. The carbon storage of mixed broadleaved forests was 138.03 Tg which ranked the largest (22.90%) among all forest types. The young and middle aged forests which accounted for 70.66% of the total carbon storage were the main body of carbon storage in Zhejiang Province. The carbon density of forest ecosystems in Zhejiang Province was 120.80 t·hm^-2 and that in tree layer, shrub-herb layer, litter layer and soil layer were 24.65 t·hm^-2, 3.36 t·hm^-2, 2.28 t·hm^-2 and 90.51 t·hm^-2, respectively. The significant relationship between soil organic carbon storage and forest ecosystem carbon storage indicated that soil carbon played an important role in shaping forest ecosystem carbon density. Carbon density of tree layer increased with age in natural forests, but decreased in the order over-mature > near-mature > mature > middle-aged > young forest in plantations. The proportions of young and middle aged forests were larger than any other age classes. Thereby, the carbon storage of forest ecosystems in Zhejiang Province could be increased through a proper forest management.     

Carbon storage of the forests and its spatial pattern in Nei Mongol,China

Aims
Forest carbon storage in Nei Mongol plays a significant role in national terrestrial carbon budget due to its large area in China. Our objectives were to estimate the carbon storage in the forest ecosystems in Nei Mongol and to quantify its spatial pattern.
Methods
Field survey and sampling were conducted at 137 sites that distributed evenly across the forest types in the study region. At each site, the ecosystem carbon density was estimated thorough sampling and measuring different pools of soil (0-100 cm) and vegetation, including biomass of tree, grass, shrub, and litter. Regional carbon storage was calculated with the estimated carbon density for each forest type.
Important findings
Carbon storage of vegetation layer in forests in Nei Mongol was 787.8 Tg C, with the biomass of tree, litter, herbaceous and shrub accounting for 93.5%, 3.0%, 2.7% and 0.8%, respectively. Carbon density of vegetation layer was 40.4 t·hm^-2, with 35.6 t·hm^-2 in trees, 2.9 t·hm^-2 in litter, 1.2 t·hm^-2 in herbaceous and 0.6 t·hm^-2 in shrubs. In comparison, carbon storage of soil layer in forests in Nei Mongol was 2449.6 Tg C, with 79.8% distributed in the first 30 cm. Carbon density of soil layer was 144.4 t·hm^-2. Carbon storage of forest ecosystem in Nei Mongol was 3237.4 Tg C, with vegetation and soil accounting for 24.3% and 75.7%, respectively. Carbon density of forest ecosystems in Nei Mongol was 184.5 t·hm^-2. Carbon density of soil layer was positively correlated with that of vegetation layer. Spatially, both carbon storage and carbon density were higher in the eastern area, where the climate is more humid. Forest reserves and artificial afforestations can significantly improve the capacity of regional carbon sink.     

Carbon storage and potentials of the broad-leaved forest in alpine region of the Qinghai- Xizang Plateau,China

Aims
Our objective was to explore the vegetation carbon storages and their variations in the broad-leaved forests in the alpine region of the Qinghai-Xizang Plateau that includes Qinghai Province and Xizang Autonomous Region.
Methods
Based on forest resource inventory data and field sampling, this paper studied the carbon storage, its sequestration rate, and the potentials in the broad-leaved forests in the alpine region of the Qinghai-Xizang Plateau.
Important findings
The vegetation carbon storage in the broad-leaved forest accounted for 310.70 Tg in 2011, with the highest value in the broad-leaved mixed forest and the lowest in Populus forest among the six broad-leaved forests that include Quercus, Betula, Populus, other hard broad-leaved species, other soft broad-leaved species, and the broadleaved mixed forest. The carbon density of the broad-leaved forest was 89.04 Mg·hm^-2, with the highest value in other hard broad-leaved species forest and the lowest in other soft broad-leaved species forest. The carbon storage and carbon density in different layers of the forests followed a sequence of overstory layer > understory layer > litter layer > grass layer > dead wood layer, which all increased with forest age. In addition, the carbon storage of broad-leaved forest increased from 304.26 Tg in 2001 to 310.70 Tg in 2011. The mean annual carbon sequestration and its rate were 0.64 Tg·a^-1 and 0.19 Mg·hm^-2·a^-1, respectively. The maximum and minimum of the carbon sequestration rate were respectively found in other soft broad-leaved species forest and other hard broad-leaved species forest, with the highest value in the mature forest and the lowest in the young forest. Moreover, the carbon sequestration potential in the tree layer of broad-leaved forest reached 19.09 Mg·hm^-2 in 2011, with the highest value found in Quercus forest and the lowest in Betula forest. The carbon storage increased gradually during three inventory periods, indicating that the broad-leaved forest was well protected to maintain a healthy growth by the forest protection project of Qinghai Province and Xizang Autonomous Region.     

Carbon storage,spatial distribution and the influence factors in Tianshan forests

Aims
Accurate estimation of carbon density and storage is among the key challenges in evaluating ecosystem carbon sink potentials for reducing atmospheric CO₂ concentration. It is also important for developing future conservation strategies and sustainable practices. Our objectives were to estimate the ecosystem carbon density and storage of Picea schrenkiana forests in Tianshan region of Xinjiang, and to analyze the spatial distribution and influencing factors.
Methods
Based on field measurements, the forest resource inventories, and laboratory analyses, we studied the carbon storage, its spatial distribution, and the potential influencing factors in Picea schrenkiana forest of Tianshan. Field surveys of 70 sites, with 800 m² (28.3 m × 28.3 m) for plot size, was conducted in 2011 for quantifying arbor biomass (leaf, branch, trunk and root), grass and litterfall biomass, soil bulk density, and other laboratory analyses of vegetation carbon content, soil organic carbon content, etc.
Important findings
The carbon content of the leaf, branch, trunk and root of Picea schrenkiana is varied from 46.56% to 52.22%. The vegetation carbon content of arbor and the herbatious/litterfall layer was 49% and 42%, respectively. The forest biomass of Picea schrenkiana was 187.98 Mg·hm^-2, with 98.93% found in the arbor layer. The biomass in all layers was in the order of trunk (109.81 Mg·hm^-2) > root (39.79 Mg·hm^-2) > branch (23.62 Mg·hm^-2) > leaf (12.76 Mg·hm^-2). From the age-group point of view, the highest and the lowest biomass was found at the mature forest (228.74 Mg·hm^-2) and young forest (146.77 Mg·hm^-2), respectively. The carbon density and storage were 544.57 Mg·hm^-2 and 290.84 Tg C, with vegetation portion of 92.57 Mg·hm^-2 and 53.14 Tg C, and soil portion of 452.00 Mg·hm^-2 and 237.70 Tg C, respectively. The spatial distribution of carbon density and storage appeared higher in the western areas than those in the eastern regions. In the western Tianshan Mountains (e.g., Ili district), carbon density was the highest, whereas the central Tianshan Mountains (e.g., Manas County, Fukang City, Qitai County) also had high carbon density. In the eastern Tianshan Mountains (e.g., Hami City), it was low. This distribution seemed consistent with the changes in environmental conditions. The primary causes of carbon density difference might be a combined effects of multiple environmental factors such as terrain, precipitation, temperature, and soil.     

Current forest carbon stocks and carbon sequestration potential in Anhui Province,China

Aims
This study was conducted to investigate carbon stocks in forest ecosystems of different stand ages in Anhui Province, and to identify the carbon sequestration potential of climax forests controlled by the natural environment conditions.
Methods
Data were collected based on field investigations and simulations were made with the BIOME4 carbon cycle model.
Important findings
Currently, the total forest carbon stocks in Anhui Province amounts to 714.5 Tg C: 402.1 Tg C in vegetation and 312.4 Tg C in soil. Generally, both the total and vegetation carbon density exhibit an increasing trend with the natural growth of forest stands. Soil carbon density increases from young to near mature forests, and then gradually decreases thereafter. Young and middle-aged forests account for 75% of the total forest area in Anhui Province, with potentially an additional 125.4 Tg C to be gained after the young and middle-aged forests reach near mature stage. Results of BIOME4 simulations show that potentially an additional 245.7 Tg C, including 153.7 Tg C in vegetation and 92 Tg C in soil, could be gained if the current forests are transformed into climax forest ecosystems in Anhui Province.     

Present status and rate of carbon sequestration of forest vegetation in Jilin Province,Northeast China

Aims
Forests represent the most important component of the terrestrial biological carbon pool and play an important role in the global carbon cycle. The regional scale estimation of carbon budgets of forest ecosystems, however, have high uncertainties because of the different data sources, estimation methods and so on. Our objective was to accurately estimate the carbon storage, density and sequestration rate in forest vegetation in Jilin Province of China, in order to understand the role of the carbon sink and to better manage forest ecosystems.
Methods
Vegetation survey data were used to determine forest distribution, size of area and vegetation types regionally. In our study, 561 plots were investigated to build volume-biomass models; 288 plots of shrubs and herbs were harvested to calculate the biomass of understory vegetation, and samples of trees, shrubs and herbs were collected to analyze carbon content. Carbon storage, density and sequestration rate were estimated by two forest inventory data (2009 and 2014), combined with volume-biomass models, the average biomass of understory vegetation and carbon content of vegetation. Finally, the distribution patterns of carbon pools were presented using ArcGIS soft ware.
Important findings
Understory vegetation biomass overall was less than 3% of the tree layer biomass, varying greatly among different forest types and even among the similar types. The carbon content of trees was between 45.80%-52.97%, and that of the coniferous forests was higher than that of the broadleaf forests. The carbon content of shrub and herb layers was about 39.79%-47.25% and 40%, respectively. Therefore, the vegetation carbon conversion coefficient was 0.47 or 0.48 in Jilin Province, and the conventional use of 0.50 or 0.45 would cause deviation of ±5.26%. The vegetation carbon pool of Jilin Province was at the upper range of regional carbon pool and had higher capacity of carbon sequestration. The value in 2009 and 2014 was 471.29 Tg C and 505.76 Tg C, respectively, and the total increase was 34.47 Tg C with average annual growth of 6.89 Tg C·a^-1. The corresponding carbon sequestration rate was 0.92 t·hm^-2·a^-1. The carbon density rose from 64.58 t·hm^-2 in 2009 to 66.68 t·hm^-2 in 2014, with an average increase of 2.10 t·hm^-2. In addition, the carbon storage of the Quercus mongolica forests and broadleaved mixed forests, accounted for 90.34% of that of all forests. The carbon increment followed the order of young > over-mature > near mature > middle-aged > mature forests. The carbon sequestration rate of followed the order of over-mature > young > near mature > middle-aged > mature forests. Both the carbon increment and the carbon sequestration rate of mature forests were negative. Furthermore, spatially the carbon storage and density were higher in the east than in the west of Jilin province, while the carbon increment was higher in northeast and middle east than in the west. The carbon sequestration rate was higher in Tonghua and Baishan in the south, followed by Jinlin in the middle and Yanbian in the east, while Baicheng and Songyuan, etc. in west showed negative values.     

Current stocks and potential of carbon sequestration of the forest tree layer in Qinghai Province,China

为阐明青海省森林生态系统乔木层植被碳储量现状及其分布特征, 该研究利用240个标准样地实测的乔木数据, 估算出青海省森林生态系统不同林型处于不同龄级阶段的平均碳密度, 并结合青海省森林资源清查资料所提供的不同龄级的各林型面积, 估算了青海省森林生态系统乔木层的固碳现状、速率和潜力。结果表明: 1) 2011年青海省森林乔木层平均碳密度为76.54 Mg·hm ^-2, 总碳储量为27.38 Tg。云杉(Picea spp.)林、柏木(Cupressus funebris)林、桦木(Betula spp.)林、杨树(Populus spp.)林是青海地区的主要林型, 占青海省森林面积的96.23%, 占青海省乔木层碳储量的86.67%, 其中云杉林的碳储量(14.78 Tg)和碳密度(106.93 Mg·hm ^-2)最高。按龄级划分, 乔木层碳储量表现为过熟林>中龄林>成熟林>近熟林>幼龄林。2)青海省乔木层总碳储量从2003年的23.30 Tg增加到2011年的27.38 Tg, 年平均碳增量为0.51 Tg·a ^-1。乔木层固碳速率为1.06 Mg·hm ^-2·a ^-1, 其中柏木林的固碳速率最大(0.44 Mg·hm ^-2·a ^-1); 桦木林的固碳速率为负值(-1.06 Mg·hm ^-2·a ^-1)。3)青海省乔木层植被固碳潜力为8.50 Tg, 其中云杉林固碳潜力最高(3.40 Tg)。该研究结果表明青海省乔木层具有较大的固碳潜力, 若对现有森林资源进行合理管理和利用, 将会增加青海省森林的碳固存能力。     

甘肃省森林碳储量现状与固碳速率

针对森林碳平衡再评估的重要性和区域尺度森林生态系统碳库量化分配的不确定性, 该研究依据全国森林资源连续清查结果中甘肃省各森林类型分布的面积与蓄积比重以及林龄和起源等要素, 在甘肃省布设212个样地, 经野外调查与采样、室内分析, 并对典型样地信息按照面积权重进行尺度扩展, 估算了甘肃省森林生态系统碳储量及其分布特征。结果表明: 甘肃省森林生态系统总碳储量为612.43 Tg C, 其中植被生物量碳为179.04 Tg C, 土壤碳为433.39 Tg C。天然林是甘肃省碳储量的主要贡献者, 其值为501.42 Tg C, 是人工林的4.52倍。天然林和人工林的植被碳密度均表现为随林龄的增加而增加的趋势, 同一龄组天然林植被碳密度高于人工林。天然林土壤碳密度从幼龄林到过熟林逐渐增加, 但人工林土壤碳密度最大值主要为近熟林。全省森林植被碳密度均值为72.43 Mg C·hm^-2, 天然林和人工林分别为90.52和33.79 Mg C·hm^-2。基于森林清查资料和标准样地实测数据, 估算出全省天然林和人工林在1996年的植被碳储量为132.47和12.81 Tg C, 2011年分别为152.41和26.63 Tg C, 平均固碳速率分别为1.33和0.92 Tg C·a^-1。甘肃省幼、中龄林面积比重较大, 占全省的62.28%, 根据碳密度随林龄的动态变化特征, 预测这些低龄林将发挥巨大的碳汇潜力。     

Soil carbon storage and its determinants in the forests of Shaanxi Province,China

Aims The bank of soil carbon of forests plays an important role in the global carbon cycle. Our aim is to understand the characteristics of soil carbon storage and its determinants in the forests in Shaanxi Province.Methods The data of forest inventory in 2009 and resampling in 2011 were used to analyze the characteristics of soil carbon storage and its determinants in the forest soil in Shaanxi Province.Important findings The soil carbon storage in the forests in Shaanxi Province was 579.68 Tg. Soil carbon storage of Softwood and Hardwood forests were the highest among all forest types, accounting for 36.35% of the whole province forest soil carbon storage. The forest soil carbon storage was 4.15 times greater in the natural forest (467.17 Tg) than that in the plantations. The young and middle-aged forests were the main contributors to the total carbon storage across all age groups, accounting for about 57.30% of the total forest soil carbon storage. The average soil carbon density of forests in Shaanxi Province was 90.68 t∙hm^-2, in which the soil carbon density of Betula forests was the highest (141.74 t∙hm^-2). Soil carbon density of different forest types were gradually decreased with soil depth. In addition, it was highest in middle-aged forest. Soil carbon density was higher in the natural forest ecosystems than that in the plantations within the each age group, indicating natural forest ecosystems have higher capacity of carbon sequestration. Differences in the spatial patterns between carbon storage and density indicated that carbon storage was related to forest coverage. The soil carbon density and storage of forests in Yulin were the lowest across the province. This suggests that, in order to enhance the regional carbon sequestration capacity in this region, we need to appropriately strengthen artificial afforestation activities and manage them scientifically and rationally. The soil carbon density of forests in Shaanxi Province decreased with the increase of longitude, latitude, and annual temperature, but increased with the increase of altitude and annual rainfall. This study provides data basis for provincial estimation of forest soil carbon bank in China.     

中国寒温带不同林龄白桦林碳储量及分配特征

为了解中国寒温带地区不同林龄白桦林生态系统碳储量及固碳能力, 在样地调查基础上, 以大兴安岭地区25、40与61年白桦(Betula platyphylla)林生态系统为研究对象, 对其乔木层、林下地被物层(灌木层、草本层、凋落物层)、土壤层(0-100 cm)碳储量与分配特征进行调查研究。结果表明白桦林乔木层各器官碳含量在440.7-506.7 g·kg ^-1之间, 各器官碳含量随着林龄的增长而降低; 灌木层、草本层碳含量随林龄的增加呈先降后升的变化趋势; 凋落物层碳含量随林龄增加而降低; 土壤层(0-100 cm)碳含量随林龄增加而显著升高, 随着土层深度的增加而降低。白桦林生态系统各层次碳储量均随林龄的增加而明显升高。25、40与61年白桦林乔木层碳储量分别为11.9、19.1和34.2 t·hm ^-2, 各器官碳储量大小顺序表现为树干>树根>树枝>树叶, 树干碳储量分配比例随林龄增加而升高。25、40与61年白桦林生态系统碳储量分别为77.4、180.9和271.4 t·hm ^-2, 其中土壤层占生态系统总碳储量的81.6%、87.7%和85.9%, 是白桦林生态系统的主要碳库。随林龄增加, 白桦林年净生产力(2.0-4.4 t·hm ^-2·a ^-1)、年净固碳量(1.0-2.1 t·hm ^-2·a ^-1)均出现增长, 老龄白桦林仍具有较强的碳汇作用。     

Effects of different rotations on carbon sequestration in Chinese fir plantations

Aims Under the context of global climate change, scientific management is the main way to enhance carbon sequestration of plantation forests. A reasonable rotation is one of the intensive management strategies, adjusting forest structure. The decline of productivity after continuous multigenerational cultivation is strongly related to its rotation. Therefore, it is necessary to study the effects of different rotations on carbon sequestration of Chinese fir (Cunninghamia lanceolata) plantations, which can provide a theoretical basis for their sustainable management.
Methods We set up sampling fields of Chinese fir plantations with different age sequences, and used the observation data to test the FORECAST model. We then simulated the effects of different rotations on Chinese fir plantations sequestration using FORECAST model.
Important findings The results showed that over a 150-year period, total carbon sequestration was highest under short rotation length (15-year). However the carbon persistence was poorest and the decline of carbon between each rotation was biggest, indicating an unsustainable management model. Compared with short rotation, the total carbon sequestration under normal rotation (25-year) and long rotation (50-year) was lower. However, the carbon persistence under long rotation was strongest, which was beneficial to maintaining carbon stability during each rotation. Under good site conditions (site index (SI) = 27), the shorter the rotation was, the more severely the soil fertility was consumed. In order to have persistent carbon sequestration rates in Chinese fir plantations, we suggest that rotation should be longer than 25 years. Application of FORECAST model can help quantitatively assess carbon sequestration capacity of forest plantations, which varies under different management strategies.     

Carbon density and its spatial distribution in the Potentilla fruticosa dominated alpine shrub in Qinghai,China

Aims Shrub recovery is recognized as an important cause of the increase of carbon stocks in China, and yet there are great uncertainties in the carbon sink capacities of shrubs. Our objectives were to estimate carbon density and its spatial distribution in alpine shrubs.
Methods Eight sites in Potentilla fruticosa dominated shrublands across Qinghai, China were investigated. Plant biomass and carbon content in leaves, branches and stems, and roots were measured to analyze the biomass allocation and carbon density.
Important findings Mean carbon densities in biological carbon, litter, soil and whole ecosystem of P. fruticosa shrublands were 5088.54, 542.1, 35903.76 and 41534.4 kg·hm^-2, respectively. Carbon density in the shrub layer was more than 68% of the biological carbon density of the whole ecosystem and was mainly distributed in roots (49.5%-56.1%). Carbon density of the herbaceous layer was 22.5% of the biological carbon density of the whole ecosystem and was also mainly distributed in roots (59.6%-75.1%). The biological carbon density of P. fruticosa shrublands (5.08 t·hm^-2) was lower than the average carbon density of shrub communities in China (10. 88 t·hm^-2). Soil carbon density contributed the largest proportion (85.8%) of total carbon density in P. fruticosa shrublands.     

Spatial pattern of soil organic carbon of the main forest soils and its influencing factors in Guangxi,China

Aims
Our objectives were to study the spatial distribution of soil organic carbon (SOC) density and its influencing factors in the main forest ecosystems in Guangxi.
Methods
A total of 345 sample plots were established in Guangxi, and the size of each plot was 50 m × 20 m. Based on the forest resource inventory data and field investigation, the SOC storage of the main forests in Guangxi was estimated. Geostatistics was applied to analyze the spatial pattern of SOC density and the main influencing factors on SOC density were also explored by principal component analysis and stepwise regression.
Important findings
The total SOC storage in the main forests in Guangxi was 1686.88 Tg, and the mean SOC density was 124.70 Mg·hm^-2, which is lower than that of China. The best fitted semivariogram model of SOC density was exponential model, and the spatial autocorrelation was medium. The contour map based on Kriging indicated that northeastern Guangxi had high SOC density and northwestern Guangxi had low SOC density, which corresponded to high SOC density in non-karst region and low SOC density in karst region. The SOC density followed the sequence of bamboo forest > deciduous broadleaf forest > warm coniferous forest > mixed evergreen and deciduous broadleaf forest > evergreen broadleaf forest, and yellow soil > red soil > lateritic red soil > limestone soil. The dominant environment factors affecting SOC density included soil depth, longitude, latitude, and altitude. Soil depth was the most influential factor, which was mainly attributed to the karst landscape.     

不同林龄、树种落叶松人工林径向生长与气候变化的关系

研究人工林径向生长与气候变化的关系对全球气候变暖背景下人工林合理经营有着重要的意义。该文对在辽东山区广泛栽培的黄花落叶松(Larix olgensis)和日本落叶松(Larix kaempferi)人工林, 运用树木年轮气候学方法建立了辽宁草河口和湾甸子林场落叶松人工林年表, 分析了落叶松径向生长对气候变化的响应以及气候条件、树种、立地条件和林分因子(林龄、密度、蓄积量等)的相对影响程度。结果发现在影响年轮-气候关系的因素中, 气象因子的潜在蒸发散(PET)的影响力最大; 林龄、密度和蓄积量同时也具有重要的影响作用。中龄落叶松人工林径向生长主要与气温呈正相关关系, 成熟落叶松人工林径向生长主要与气温呈负相关关系; 而其他因素, 如树种、立地条件等的影响作用不大。这表明在气候变暖背景下随着林龄增加, 林分会逐渐受到气温升高导致的水分亏缺的限制, 导致明显的生长下降趋势, 因而气候变暖对成熟落叶松人工林威胁更为严重, 所以要注重对成熟林的优先保护, 同时可以预测, 随着东北地区今后气候进一步变暖, 可能将逐步影响到林龄更小的林分的生长, 因此需要进一步研究如何在落叶松人工林经营中采取科学的措施来更好地应对未来气候变化。     

浙江省森林生态系统碳储量及其分布特征

利用2011-2012年野外标准地实测资料, 结合第八次全国森林资源清查资料, 研究了浙江省森林生态系统碳储量及其分布特征。结果表明: 浙江省森林生态系统碳储量为602.73 Tg, 其中乔木层、灌草层、凋落物层和土壤层碳储量分别为122.88 Tg、16.73 Tg、11.36 Tg和451.76 Tg, 分别占生态系统碳储量的20.39%、2.78%、1.88%和74.95%; 在各森林类型中, 阔叶混交林碳储量为138.03 Tg, 所占比例最大(22.90%); 在森林各龄组中, 幼、中龄林约占浙江省森林生态系统碳储量的70.66%, 是碳储量的主要贡献者。浙江省森林生态系统平均碳密度为120.80 t·hm^-2, 乔木层、灌草层、凋落物层和土壤层碳密度分别为24.65 t·hm^-2、3.36 t·hm^-2、2.28 t·hm^-2和90.51 t·hm^-2。浙江省森林生态系统土壤层碳储量和生态系统碳储量呈极显著相关关系, 说明土壤层碳储量对浙江省森林生态系统碳储量贡献较大。浙江省天然林乔木层碳密度整体表现为过熟林>成熟林>近熟林>中龄林>幼龄林, 而人工林乔木层碳密度表现为过熟林>近熟林>成熟林>中龄林>幼龄林。浙江省幼、中龄林林分面积占比重较大, 占全省森林面积的76.76%, 若对现有森林进行更好的经营和管理, 可以增加浙江省森林的碳固存能力。     

氮磷添加及林分密度对大叶相思林土壤化学性质的影响

大气氮(N)沉降随着人类的活动而日趋严重, 加上中国热带亚热带红壤普遍缺磷(P), 许多森林生态系统由于广泛使用磷肥而产生P富集, 直接影响了森林土壤化学特性。林分密度改变林地的光照、温度、湿度和凋落物持水量, 从而影响土壤特性。为了解外源性N和P添加与林分密度对大叶相思(Acacia auriculiformis)林地土壤化学性质的影响, 为大叶相思人工林的种植密度和土壤养分管理提供科学依据, 该研究于2013到2015年, 以4种不同密度(1 667、2 500、4 444和10 000 trees·hm ^-2)的10年生大叶相思人工林为研究对象, 分别进行添加N、P和N+P处理, 在试验结束时采集0-10 cm土壤, 对其pH、有机质含量、N含量、P含量和钾(K)含量进行了测定分析。结果表明: 施N和N+P均显著降低了土壤的pH和速效K含量, 显著提高了林地土壤的碱解N含量。施N还显著提高了林分土壤的全N含量, 施P显著提高了土壤pH, 降低了林分土壤的全N含量。施P和N+P显著提高了土壤有机质、全P和有效P含量。随着林分密度的增加, 各处理的土壤有机质、全N、碱解N、全P、有效P和速效K含量显著提高。N、P添加处理和密度处理对大叶相思林的土壤pH、有机质和N、P、K含量有显著的交互作用。总体来看, N添加、P添加、林分密度及其交互作用对大叶相思的土壤化学性质有显著影响。     

Research on characteristics of biomass distribution in urban forests of Shanghai metropolis based on remote sensing and spatial analysis

Aims
Monitoring and quantifying the biomass and its distribution in urban trees and forests are crucial to understanding the role of vegetation in an urban environment. In this paper, an estimation method for biomass of urban forests was developed for the Shanghai metropolis, China, based on spatial analysis and a wide variety of data from field inventory and remote sensing.
Methods
An optimal regression model between forest biomass and auxiliary variables was established by stepwise regression analysis. The residual value of regression model was computed for each of the sites sampled and interpolated by Inverse-distance weighting (IDW) to predict residual errors of other sites not subjected to sampling. Forest biomass in the study area was estimated by combining the regression model based on remote sensing image data and residual errors of spatial distribution map. According to the distribution of plantations and management practices, a total of 93 sample plots were established between June 2011 and June 2012 in the Shanghai metropolis. To determine a suitable model, several spectral vegetation indices relating to forest biomass and structure such as normalized difference vegetation index (NDVI), ratio vegetation index (RVI), difference vegetation index (DVI), soil-adjusted vegetation index (SAVI), and modified soil-adjusted vegetation index (MSAVI), and new images synthesized through band combinations such as the sum of TM2, TM3 and TM4 (denoted Band 234), and the sum of TM3, TM4 and TM5 (denoted Band 345) were used as alternative auxiliary parameters .
Important findings
The biomass density in urban forests of the Shanghai metropolis varied from 15 to 120 t·hm^-2. The higher densities of forest biomass concentrated mostly in the urban areas, e.g. in districts of Jing’an and Huangpu, mostly ranging from 35 to 70 t·hm^-2. Suburban localities such as the districts of Jiading and Qingpu had lower biomass densities at around 15 to 50 t·hm^-2. The biomass density of Cinnamomum camphora trees across the Shanghai metropolis varied between 20 and 110 t·hm^-2. The spatial biomass distribution of urban forests displayed a tendency of higher densities in northeastern areas and lower densities in southwestern areas. The total biomass was 3.57 million tons (Tg) for urban forests and 1.33 Tg for C. camphora trees. The overall forest biomass was also found to be distributed mostly in the suburban areas with a fraction of 93.9%, whereas the urban areas shared a fraction of only 6.1%. In terms of the areas, the suburban and urban forests accounted for 95.44% and 4.56%, respectively, of the total areas in the Shanghai metropolis. Among all the administrative districts, the Chongming county and the new district of Pudong had the highest and the second highest biomass, accounting for 20.1% and 19.18% of the total forest biomass, respectively. In contrast, the Jing’an district accounted for only 0.11% of the total forest biomass. The root-mean-square error (RMSE), mean absolute error (MAE) and mean relative error (MRE) of the model for estimating urban forest biomass in this study were 8.39, 6.86 and 24.22%, respectively, decreasing by 57.69%, 55.43% and 64.00% compared to the original simple regression model and by 62.21%, 58.50%, 65.40% compared to the spatial analysis method. Our results indicated that a more efficient way to estimate urban forest biomass in the Shanghai metropolis might be achieved by combining spatial analysis with regression analysis. In fact, the estimated results based on the proposed model are also more comparable to the up-scaled forest inventory data at a city scale than the results obtained using regression analysis or spatial analysis alone.     

甘肃省5种典型人工林生态系统固碳现状与潜力

基于野外调查与室内实测数据,结合第八次全国森林资源清查资料,分析了甘肃省5种典型人工林生态系统(刺槐、杨树、油松/华山松、落叶松及云杉林)森林生态系统碳密度、碳储量,并估算了乔木层固碳潜力.结果表明: 5种典型人工林生态系统平均碳密度和总碳储量分别为139.65 t·hm^-2和85.78 Tg,不同人工林类型之间差异较大.不同龄组间碳密度表现为近熟林(250.70 t·hm^-2)最大,其次是成熟林(175.97 t·hm^-2)和中龄林(156.92 t·hm^-2),幼龄林(117.56 t·hm^-2)最低.碳储量表现为幼龄林(45.47 Tg)>中龄林(19.54 Tg)>成熟林(11.84 Tg)>近熟林(8.93 Tg),幼中龄林碳储量占总碳储量的75.9%.5种典型人工林乔木层现实固碳潜力合计为7.27 Tg,刺槐林(2.49 Tg)和杨树林(2.10 Tg)最大;各龄组中,幼龄林现实固碳潜力最大(3.78 Tg),其次是中龄林(2.04 Tg),近熟林最小(0.45 Tg).5种典型人工林乔木层最大固碳潜力达27.55 Tg,表现为刺槐林(9.42 Tg)>落叶松林(6.22 Tg)≈云杉林(6.36 Tg)>杨树林(3.18 Tg)>油松/华山松林(2.37 Tg);其中,幼、中龄林最大固碳潜力分别为18.48和6.89 Tg,占总最大固碳潜力的92%.