Forest Vegetation Carbon Storage Research Articles

Changes in Forest Vegetation Carbon Storage and Its Driving Forces in Subtropical Red Soil Hilly Region over the Past 34 Years: A Case Study of Taihe County, China

After decades of afforestation, China’s forest coverage has increased significantly, but the forest quality and its impact on ecosystem services are still controversial. Taking forest vegetation carbon storage as an example, most assessment results based on the national forest inventory data showed that the contribution of enlarged forest area to the increase in China’s forest vegetation carbon storage was higher than that of the change in forest quality (vegetation carbon density). This means that the increase in forest carbon storage in China was mostly contributed by the increase in forest area and was less due to the increased forest vegetation carbon density. However, the national forest inventory data are based on national permanent plots that may be protected or are less disturbed to some extent. Therefore, the contribution of the change in forest quality to the increase in forest vegetation carbon storage, as evaluated from the national forest inventory data, might be overestimated, especially in regions with frequent human activities. To test the hypothesis, we selected Taihe County, a typical representative of the red soil hilly region in subtropical China, where the population is dense, economic development is fast, and the forest has experienced destruction and re-establishment. To accurately assess the impact of changes in the forest area and forest quality on forest vegetation carbon storage variation in real situations, we collected and used a series of remote sensing images from 1986 to 2019, inventory data for forest management, and field data. The results showed that the forest area and forest vegetation carbon density increased from 10.85 × 104 ha and 17.89 Mg/ha in 1986 to 16.40 × 104 ha and 26.51 Mg/ha in 2019, with an increase of 51.11% and 48.23%, respectively. Meanwhile, the forest vegetation carbon storage increased by 123.99%, from 1.94 Tg in 1986 to 4.35 Tg in 2019, suggesting a significant carbon sequestration ability. Further analysis showed that the contributions of changes in forest area and forest quality to the forest vegetation carbon storage variation were 1.23 Tg (51.19%) and 1.17 Tg (48.81%), respectively. The result implies that the increase in forest area and forest quality almost contributed equally to the increase in forest vegetation carbon storage during the 34 years of vegetation restoration in Taihe County. However, forest vegetation carbon density controlled the variation of forest vegetation carbon storage in all three forest developing stages. The precision of our results was also tested with two inventory datasets for forest management in Taihe County in 2009 and 2019. The relative contribution of forest vegetation carbon density is lower than most of the previous study results using national forest inventory data in this region, indicating that the contribution of change in the forest vegetation carbon density to the forest vegetation carbon storage variation might be overestimated based on these national permanent plots, which were protected or less disturbed to some extent.

Spatial variation analysis of urban forest vegetation carbon storage and sequestration in built-up areas of Beijing based on i-Tree Eco and Kriging

To explore available methods for assessing the orientation, magnitude, and role of urban forests in abating climate change, i-Tree Eco and Kriging interpolation were employed to quantify and map the carbon storage and sequestration capability of trees in urban forests. Specifically, urban tree field data were collected from 981 sample plots throughout five types of urban forests in the built-up area of Beijing, China, and used to estimate carbon storage and sequestration within each individual plot and the area as a whole. These data were subsequently subjected to Kriging interpolation to map carbon storage and sequestration within the study area. The results showed that the carbon storage and sequestration patterns in the urban forests in Beijing exhibit noticeable spatial heterogeneity, and that there is a clear, statistically significant distribution of high and low value areas. Furthermore, urban planning, the degree of urbanization, and the urban forest structure effect the carbon spatial distribution. This work provides a reference for prudent planning and construction of urban forests and will aid decision-makers in designing eco-friendly urban environments.

Effects of Stand Structure and Topography on Forest Vegetation Carbon Density in Jiangxi Province

Stand structure and topography are important factors affecting forest vegetation carbon density (FVCD). Revealing the interaction mechanisms between stand structure and topography on FVCD is of great significance for enhancing forest vegetation carbon storage and achieving regional carbon neutrality. Based on stratified sampling, systematic distribution and forest continuous inventory sample plots in Jiangxi province, the variation characteristics of FVCD and its correlations with stand structure and topographic factors were studied. The results are as follows: (1) The average FVCD in Jiangxi province was 44.23 Mg/ha, which was dominated by the carbon density of the arbor layer, accounting for about 81.39% of the total forest—far lower than the average level of global FVCD, which proved that the forest in Jiangxi province was dominated by middle-age and young forests with low carbon density, and also showed that the potential for forest vegetation carbon storage in Jiangxi province was huge. (2) Except for vegetation carbon densities of shrub and herb layers, the vegetation carbon densities of other forest layers in Jiangxi province were significantly different among different forest types. Volume per unit area was the most important factor affecting the vegetation carbon densities of arbor and total forest, and vegetation carbon density–volume models of the main forests were built for vegetation carbon density calculation in Jiangxi province. (3) The vegetation carbon densities of arbor layer, snag and log layer, and total forest increased significantly with increases in elevation and slope. Except for the shrub layer and herb layer, the vegetation carbon densities of the other layers and the total forest had extremely significant or significant differences between slope position gradients—indicating that the effect of topography on FVCD in Jiangxi province was significant, mainly through influencing of forest distribution and human disturbance intensity.

Contributions of National Key Forestry Ecology Projects to the forest vegetation carbon storage in China

Planted forests in China have continuously stored large amounts of vegetation carbon since the implementation of the National Key Forestry Ecology Projects (NKFEPs). However, the time variation of the contribution of NKFEP-covered planted forests to the national forest vegetation carbon storage has not been systematically documented. Moreover, predicting the future vegetation carbon storage of NKFEP-covered planted forests is of great significance for global climate change. Thus, we collected vegetation carbon density data on China’s forests from 251 published articles to clarify the contributions and vegetation carbon sequestration potential of NKFEP-covered planted forests. The results showed that the vegetation carbon density of NKFEP-covered planted forests ranged from 23.49 to 68.88 Mg ha−1, that slight differences existed among the NKFEP-covered planted forests during 2009–2018, and that slight changes occurred from 1989 to 2018. The total contribution rate of NKFEP-covered planted forests to China’s forest vegetation carbon storage was 36.29% during 2009–2018, and the contribution rates of most NKFEPs during 2009–2018 were higher than those during 1999–2008. The total vegetation carbon sequestration potential ranged from 4.22 to 8.67 Pg under four scenarios, in which NKFEP-covered planted forests contributed 40%, 60%, 80% and 100% of the vegetation carbon storage of natural forests in the corresponding NKFEP regions, respectively. These results indicate that NKFEP-covered planted forests significantly contribute to the vegetation carbon storage of China’s forests, and that NKFEP-covered planted forests have large vegetation carbon sequestration potential, which is beneficial for future national and global forest carbon fixation.

川西米亚罗自然保护区森林地上碳储量遥感估算

PDF HTML阅读 XML下载 导出引用 引用提醒 川西米亚罗自然保护区森林地上碳储量遥感估算 DOI: 10.5846/stxb201807281610 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 四川省科技厅应用基础项目（2017JY0155）；四川省中医药管理局重大专项（2018PC005） Estimation of forest aboveground carbon storage in Sichuan Miyaluo Nature Reserve based on remote sensing Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:研究米亚罗自然保护区的森林地上碳储量，有利于掌握高山峡谷区森林植被碳储量的分布特点，对区域森林资源的有效科学管理和维护森林生态环境具有重要意义。通过对保护区内的7个主要树种分别构建模型来初步估测森林地上碳储量，利用实地调查的样地数据与同期Landsat 8遥感卫星影像，得到波段信息、植被指数、主成分分析、纹理特征、地形因子、植被生长六大类共80个因子，用以构建乔木层不同树种地上碳储量的多元线性逐步回归模型，而灌木层的碳储量则由生物量密度法估算得出。研究结果表明：①模型预测值与实测值相关系数在0.675-0.775之间，精度较高，预测结果可靠；②米亚罗自然保护区森林地上碳储量为5.861 Tg，其中乔木层5.632 Tg，灌木层0.229 Tg。云冷杉林是研究区分布最广的林分类型，其碳储量为5.098 Tg，占森林地上碳储量总量的86.98%，在维持区域碳平衡方面发挥着重要作用。③研究区森林平均碳密度为53.138 t/hm2，其中冷杉的碳密度最高，达到74.467 t/hm2。④区域内森林地上碳储量以杂谷脑河流域及支流为中心，以一定缓冲距离呈树枝状发散分布，海拔3000-4000 m区域的森林植被碳储量最大，且阴坡的碳储量明显高于阳坡。 Abstract:The Miyaluo Nature Reserve is an important carbon sequestration region in Western Sichuan. Study of aboveground forest carbon storage in Miyaluo Nature Reserve is necessary for elucidating the distribution characteristics of forest vegetation carbon storage in alpine gorge areas. Furthermore, it is of great significance to the scientific management of forest resources and the maintenance of forest ecological environments in the nature reserves. In this study, carbon storage models were established for seven main tree species to estimate the carbon storage on forest land. Firstly, 897 samples were obtained from a field survey, and sample biomass and carbon storage were calculated based on the volume-derived biomass method. Secondly, Landsat 8 satellite remote sensing data were used to obtain image characteristics of forest vegetation. Thirdly, combined with forest survey data, 80 factors were determined that were classified into six categories (band information, vegetation index, principal component analysis, texture features, topographic factors, and vegetation growth). Moreover, the correlation between these factors and the biomass of different tree species was analyzed, according to the order of Pearson's correlation coefficient, the significant correlation factors were then introduced into the multiple linear stepwise regression equation as independent variables, and the estimation models of aboveground carbon storage of different tree species in the tree layer were established. Finally, the aboveground carbon storage of the arbor layer was calculated by the estimation model, and the carbon storage in the shrub layer was calculated using the average biomass density method. The results showed that ① the accuracy of models for carbon storage estimation was within the margin of error, and the correlation coefficient between the measured value and the predicted value of the model was 0.675-0.775. ② The total carbon storage in the forest in the Miyaluo Nature Reserve was 5.861 Tg, of which the aboveground carbon storage in the arbor layer was 5.632 Tg, and the carbon storage in the shrub layer was 0.229 Tg. The order of the aboveground carbon storage of the prominent species was Abies faberi > Picea asperata > Tsuga chinensis > Larix gmelimi > Quercus acutissima > Betula chinensis > Pinus tabulaeformis > Pinus armandi; The total carbon storage of fir trees was 5.098 Tg, accounting for 86.98% of the aboveground carbon storage in the study area. The spruce-fir forest was the most widely distributed forest type in the Miyaluo Nature Reserve, and it played an important role in maintaining the carbon balance. ③ The average carbon density in the forest in Miyaluo Nature Reserve was 53.138 t/hm2, and the carbon density of Chinese fir species was higher than the average. The carbon density of fir was much higher than that of other tree species and was 74.467 t/hm2. ④ The spatial distribution characteristics of aboveground forest carbon storage in the study area were obtained by overlapping the Digital Elevation Model (DEM) with carbon storage. Taking the Zagunao River and its tributaries as the center, the carbon storage spatial distribution data were extended to the surrounding area by a given buffer distance in the whole region, similar to arborization. The largest area of forest vegetation carbon storage was distributed in regions with elevation of 3000-4000 m. The aboveground carbon storage on shady slopes was higher than that on sunny slopes. 参考文献 相似文献 引证文献

Estimation of forest vegetation carbon storage in Hunan Province, China based on k-NN method and domestic high-resolution data

To promote the application of domestic high-resolution satellite data in large-scale carbon storage estimation and measurement, a total of 206 high-resolution remote sensing images covering Hunan Province were used as the data source, and the estimated minimum unit was fixed as a 0.06 hm2 square composed of multiple pixels. Through the establishment and purification of the interpretation marks, in the extraction of forest information, the pixel-based method and object-oriented classification method were used to compare. In the estimation of carbon storage of arbor forest, the robust estimate, partial least squares method and k-NN estimate were used to compare. Finally, we estimated forest carbon storage in Hunan Province and generated the distribution map of carbon density levels. The results showed that the interpretation mark based on the automatic extraction of plots could increase the extraction accuracy of arbor forest after purification. For the estimation of forest carbon storage at large-scale, the k-NN algorithm embodied a large advantage in forest information extraction and arbor forest carbon storage modeling. The average classification accuracy of the 206 scene images was 76.8%, the average RMSE was 8.95 t·hm-2, the average RRMSE was 19.1%, and the total carbon stock in Hunan Province was 22.28 Mt. The results provided effective reference for the estimation and measurement of forest carbon storage at the provincial and national scales.

基于森林清查资料的河南省森林植被碳储量动态变化

PDF HTML阅读 XML下载 导出引用 引用提醒 基于森林清查资料的河南省森林植被碳储量动态变化 DOI: 10.5846/stxb201807081487 作者: 作者单位: 河南科技大学,河南科技大学,河南科技大学,河南科技大学,河南科技大学 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（31700367）；河南省高等学校青年骨干教师培养计划项目（2016GGJS-062）；河南科技大学学科提升振兴A计划项目（13660001，13660002）；河南科技大学博士科研启动基金（4024-13480081） Dynamic of forest vegetation carbon storage in He'nan Province based on forest inventory data Author: Affiliation: Henan University of Science and Technology,Hean University of Science and Technology,,, Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:利用1994-1998年、1999-2003年、2004-2008年、2009-2013年河南省4期森林资源清查数据，运用生物量转换因子连续函数法和平均生物量法，估算了1998-2013年河南省森林植被的碳储量和碳密度变化。研究结果表明，河南省森林植被碳储量由1998年的45.57 Tg增加到2013年的107.98 Tg，年均碳汇量为4.16 Tg/a。乔木林碳储量和碳密度分别由1998年的33.54 Tg和22.39 Mg/hm2增加到2013年的97.11 Tg和31.80 Mg/hm2。乔木林碳储量在所有植被类型中占主体，4个森林清查时期乔木林碳储量占森林植被总碳储量的比例分别为73.60%、79.22%、85.63%和89.93%。2013年森林清查时，乔木林中杨树和栎类碳储量最大，分别占总碳储量的37.61%和25.22%，各龄组乔木林碳密度大小顺序依次为成熟林 > 近熟林 > 中龄林 > 过熟林 > 幼龄林。阔叶林面积、碳储量、碳密度均高于针叶林，阔叶林是河南省森林碳汇的主要贡献者。人工林面积、碳储量、碳密度增加幅度都要高于天然林，人工林碳储量由1998年的9.62 Tg增加到2013年的55.67 Tg，占乔木林碳储量总增量的77.15%，人工林碳密度由1998年的17.86 Mg/hm2提高到2013年的32.01 Mg/hm2，人工林在河南省森林碳汇中逐步发挥重要的作用，逐渐成为河南省森林碳汇的主体，随着人工林生长为具有较高碳密度的成熟林，河南省乔木林将具有较大的碳汇潜力。 Abstract:Based on the forest resources inventory data of 1994-1998, 1999-2003, 2004-2008, and 2009-2013 in He'nan Province, the dynamic changes in forest vegetation carbon storage and density between 1998 and 2013 were estimated by using the continuous biomass expansion factor method and average biomass method. The results showed that the carbon storage of forest vegetation in the He'nan Province increased from 45.57 Tg in 1998 to 107.98 Tg in 2013, with an annual carbon sink of 4.16 Tg year-1. The carbon storage and density of arbor forests increased from 33.54 Tg and 22.39 Mg hm-2 in 1998 to 97.11 Tg and 31.80 Mg hm-2 in 2013, respectively. The carbon storage of arbor forests comprised the largest proportion of storage for all vegetation types; the proportion of carbon storage of arbor forests to total carbon storage of forest vegetation in the four forest inventory periods was 73.60%, 79.22%, 85.63%, and 89.93%, respectively. In 2013, Populus and Quercus had the largest carbon storage, accounting for 37.61% and 25.22% of the total carbon storage in arbor forests, respectively. The carbon density of arbor forests in each age group was ranked in the following order:mature forest > premature forest > middle-aged forest > over-mature forest > young-aged forest. The area, carbon storage and carbon density of broad-leaved forests were higher than those of coniferous forests, and broad-leaved forests were the main contributor to the forest carbon sink in He'nan Province. The area, carbon storage and carbon density of the planted forests increased more than the natural forests. The carbon storage of planted forests increased from 9.62 Tg in 1998 to 55.67 Tg in 2013, accounting for 77.15% of the total increment of carbon storage in arbor forests. The carbon density of planted forests increased from 17.86 Mg hm-2 in 1998 to 32.01 Mg hm-2 in 2013. The importance of the role of planted forests in the forest carbon sink of He'nan Province is gradually emerging. As the planted forests grow into mature forest with a high carbon density, the arbor forests in He'nan Province will have greater carbon sequestration potential. 参考文献 相似文献 引证文献

Dynamics of forest biomass carbon stocks from 1949 to 2008 in Henan Province, east-central China

We estimated forest biomass carbon storage and carbon density from 1949 to 2008 based on nine consecutive forest inventories in Henan Province, China. According to the definitions of the forest inventory, Henan forests were categorized into five groups: forest stands, economic forests, bamboo forests, open forests, and shrub forests. We estimated biomass carbon in forest stands for each inventory period by using the continuous biomass expansion factor method. We used the mean biomass density method to estimate carbon stocks in economic, bamboo, open and shrub forests. Over the 60-year period, total forest vegetation carbon storage increased from 34.6 Tg (1 Tg = 1 × 1012 g) in 1949 to 80.4 Tg in 2008, a net vegetation carbon increase of 45.8 Tg. By stand type, increases were 39.8 Tg in forest stands, 5.5 Tg in economic forests, 0.6 Tg in bamboo forests, and −0.1 Tg in open forests combine shrub forests. Carbon storage increased at an average annual rate of 0.8 Tg carbon over the study period. Carbon was mainly stored in young and middle-aged forests, which together accounted for 70–88% of the total forest carbon storage in different inventory periods. Broad-leaved forest was the main contributor to forest carbon sequestration. From 1998 to 2008, during implementation of national afforestation and reforestation programs, the carbon storage of planted forest increased sharply from 3.9 to 37. 9 Tg. Our results show that with the growth of young planted forest, Henan Province forests realized large gains in carbon sequestration over a 60-year period that was characterized in part by a nation-wide tree planting program.

福州市森林碳储量定量估算及其对土地利用变化的响应

PDF HTML阅读 XML下载 导出引用 引用提醒 福州市森林碳储量定量估算及其对土地利用变化的响应 DOI: 10.5846/stxb201502110337 作者: 作者单位: 复旦大学环境科学与工程系,复旦大学环境科学与工程系,复旦大学环境科学与工程系,复旦大学环境科学与工程系 作者简介: 通讯作者: 中图分类号: 基金项目: The quantitative estimation of forest carbon storage and its response to land use change in Fuzhou, China Author: Affiliation: Department of Environmental Science and Engineering,Fudan University,Department of Environmental Science and Engineering,Fudan University,Department of Environmental Science and Engineering,Fudan University,Department of Environmental Science and Engineering,Fudan University Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:基于RS与GIS技术，以遥感影像数据、土地利用数据、森林资源二类调查数据为主要数据源，采用逐步回归法建立森林蓄积量定量估测模型。根据“蓄积量-生物量-碳储量”推算方法，对福州市森林植被碳储量和碳密度进行估算。建立福州市土地利用转移矩阵，分析2000-2010年土地利用变化影响下的福州市森林碳储量变化特征。结果表明：（1）根据不同的森林类型，即常绿阔叶林、常绿针叶林、针阔混交林分别建立的多元线性回归模型修正决定系数分别为0.599、0.679、0.694，通过模型适用性检验和精度验证。（2）2000年、2010年福州市森林植被碳储量总量分别为12.499Tg、12.642Tg，植被碳密度分别为18.694、18.708 t/hm2，森林植被碳储量增加了1.430×105 t。（3）福州市闽清县、永泰县、闽侯县的森林植被碳密度常年保持较高水平，并呈现出增长趋势；罗源县、长乐市、连江县森林植被碳密度较低，并呈现下降趋势。（4）2000-2010年，灌木和耕地是主要土地利用类型转出者，森林和建设用地是主要土地利用类型转入者。森林主要由灌木和耕地转化，主要向建设用地、耕地进行转化。由于土地利用变化，10年间福州市总碳储量减少了1.711×104 t，其中土壤碳储量减少2.230×103 t，植被碳储量减少1.489×104 t。 Abstract:In this study, remote sensing (RS) images, land-use data, and forest resource inventory data were used to build a quantitative estimation model of forest volume via the stepwise regression method. The carbon storage and carbon density of forest vegetation in Fuzhou from 2000 to 2010 were analyzed using the Biomass Expansion Factor (BEF) method to correlate forest volume with volume, biomass and carbon storage. A land use transition matrix was created, and used to study the variation of forest carbon storage in response to land use change in Fuzhou. The results showed that:(1) the results of quantitative estimation models of forest volume which were build according to different type of forest (Evergreen broad-leaved forest, Evergreen coniferous forest, Mixed broadleaf-conifer forest) turned out the effects with the adjusted R2 being 0.599, 0.679, 0.694 respectively. All quantitative estimation models of forest volume passed the applicability and accuracy test. The calculated total forest volume in Fuzhou was 2.097×107 m3 in 2000 and 2.594×107 m3 in 2010, revealing an increase in volume over the course of a decade. Of all the geographical subdivisions of Fuzhou, Yongtai County maintained the greatest forest volume throughout the decade, while Changle County contained the lowest forest volume. (2) Total carbon storage by forest vegetation in Fuzhou city was 12.499 Tg in 2000 and 12.642 Tg in 2010. Thus, in ten years, forest vegetation carbon storage increased by 1.430×105 t. The vegetation carbon densities in 2000 and 2010 were 18.694 t/hm2 and 18.708 t/hm2, respectively. (3) The carbon density of forest vegetation in Minqing County, Yongtai County, and Minhou County, which are located in western Fuzhou, remained high during this ten year period, and was observed to increase overall. In contrast, Luoyuan County, Changle County, and Lianjiang County, which are located in eastern Fuzhou, experienced declines in the carbon density of forest vegetation, as a result of increasing socio-economic and anthropogenic activity. (4) In these areas, the forest was mostly converted to shrub and crop land between 2000 and 2010. As a result of this change in land use, forest carbon storage in Fuzhou declined by 1.711×104 t overall. In addition, soil carbon storage and plant carbon storage decreased by 2.230×103 t and 1.489×104 t, respectively. 参考文献 相似文献 引证文献

基于VAR模型的森林植被碳储量影响因素分析——以陕西省为例

Forest vegetation carbon dynamics are widely considered as basic indicators of the capacity of a forest ecosystem for carbon sequestration and carbon exchange with the atmosphere and the ability of the forest ecosystem to function as a carbon sink or source. Forest management practices such as harvesting,afforestation,and reforestation are the most important factors that influence forest carbon dynamics. Therefore,elucidation of the effects of human silvicultural activities on forest ecosystem dynamics will provide a valuable insight into ways of expanding the size of the carbon pool and improvingthe ecological environment of China. Previous studies have attempted to identify the factors that affect forest carbon sequestration; however,most of these investigations focused on a single factor and did not consider the interactions occurring between multiple factors. In addition, most previous studies were conducted on a small scale, and no investigations conducted at a regional or larger scale examined the influence of interactions occurring between multiple factors on forest carbon sequestration. Forest dynamic models represent a valuable tool for resolving this problem; however,existing models do not adequately reflect the interactive effects of multiple factors such as forest management practices,climate change,and other human-induced disturbances on forest carbon storage. In the present study,we used a vector autoregression( VAR) model that included seven parameters( factors)( timber output,forest-tending area,area affected by forest diseases and / or pests,fire-affected area,reforestation area,annual total precipitation,and annual average temperature) to simulate forest carbon storage dynamics in Shanxi Province. The results of variable stationary and cointegration analyses revealed that the investigated variables exhibited a single whole-sequence order at the 5% significance level; in addition,they showed long-term stable equilibrium. Hence,we applied each variable to the VAR model and used the model stationary test to show that all the characteristic roots of the VAR model were 1,i.e.,these roots fell within the unit circle. Our results indicate that the VAR model system is stable and meets the prerequisites for identifying the effects of multiple factors on forest vegetation carbon storage dynamics. Finally,we used impulse response and variance decomposition analyses to show that forest pests and timber output had significant negative impacts on carbon storage and contributed to a high degree of 5. 61% and 4. 52%,respectively. Forest tending and artificial reforestation had weakly negative effects on carbon storage,whereas forest fires,precipitation,and temperature had no significant effects on carbon storage. Taken together,our findings verify the suitability of the VAR model for identifying the effects of multiple factors on forest ecosystem carbon storage dynamics. Therefore,in future studies,this model can be used to analyze factors that influence forest vegetation carbon storage at a provincial scale.

Temporal and Spatial Distribution Pattern of Carbon Sink in Forest Vegetation of Jiangxi Province

Forest ecosystem has a huge carbon sink function and plays an inhibitory effect on global climate warming. The carbon storages of Jiangxi province forest vegetation between 1984 and 2003 were estimated by an age-based volume-to-biomass method according to the forest resource inventory data of the homologous periods. The results showed that the total vegetation carbon storage of Jiangxi province forest vegetation in the four periods was 101.86TgC, 124.1TgC, 157.3TgC and 188.78TgC respectively. The total vegetation carbon storage of Jiangxi province forests had increased 86.92TgC and accumulated about 4.35TgC per year from 1984 to 2003. The average forest vegetation carbon density was between 22.77t/hm2 and 25.94t/hm2. The spatial pattern of forest vegetation carbon storage in Jiangxi province was studied according to forest resources survey data during 10th five-year plan. The results showed that the largest forest vegetation carbon storage was the Ganzhou city (62.36TgC) and the least was Nanchang city (1.72TgC). The average carbon intensity of all city forest vegetation in Jiangxi province was roughly from 20.641t/hm2 to 32.930t/hm2. The smallest carbon density was Nanchang city (20.641t/hm2) while the biggest was Jingdezhen city (32.930t/hm2).

Combining LPJ-GUESS and HASM to simulate the spatial distribution of forest vegetation carbon stock in China

It is very important in accurately estimating the forests' carbon stock and spatial distribution in the regional scale because they possess a great rate in the carbon stock of the terrestrial ecosystem. Yet the current estimation of forest carbon stock in the regional scale mainly depends on the forest inventory data, and the whole process consumes too much labor, money and time. And meanwhile it has many negative influences on the forest carbon storage updating. In order to figure out these problems, this paper, based on High Accuracy Surface Modeling (HASM), proposes a forest vegetation carbon storage simulation method. This new method employs the output of LPJ-GUESS model as initial values of HASM and uses the inventory data as sample points of HASM to simulate the distribution of forest carbon storage in China. This study also adopts the seventh forest resources statistics of China as the data source to generate sample points, and it also works as the simulation accuracy test. The HASM simulation shows that the total forest carbon storage of China is 9.2405 Pg, while the calculated value based on forest resources statistics are 7.8115 Pg. The forest resources statistics is taken based on a forest canopy closure, and the result of HASM is much more suitable to the real forest carbon storage. The simulation result also indicates that the southwestern mountain region and the northeastern forests are the important forest carbon reservoirs in China, and they account for 39.82% and 20.46% of the country's total forest vegetation carbon stock respectively. Compared with the former value (1975-1995), it manifests that the carbon storage of the two regions do increase clearly. The results of this research show that the large-scale reforestation in the last decades in China attains a significant carbon sink.

Potential for forest vegetation carbon storage in Fujian Province, China, determined from forest inventories

Carbon storage in forest vegetation of Fujian Province plays a significant role in the terrestrial carbon budget in China. The purposes of this study are: (1) to evaluate how the afforestation and reforestation programs established in Fujian Province influence carbon storage in forest ecosystems; (2) to assess the influence of tree species, forest age and ownership changes on vegetation carbon storage; and (3) to explore strategies for increasing vegetation carbon potentials. Data from seven Chinese Forest Resource Inventories and 5,059 separate sample plots collected between 1978 and 2008 were used to estimate vegetation carbon storage in the whole province. In addition, uncertainty analysis was conducted to provide the range of our estimations. Total forest vegetation carbon storage increased from 136.51 in 1978 to 229.31 Tg C in 2008, and the forest area increased from 855.27 × 104 to 1,148.66 × 104 ha, showing that the Fujian forests have a net vegetation carbon increase of 96.72 Tg C with an annual increase of 4.84 Tg C over the study period. Carbon storage varied with dominant forest species, forest age and forest ownership, suggesting that increases in vegetation carbon potentials can be achieved through selection of forest species and management of age structures. Implementation of afforestation and reforestation programs in Fujian Province over the past three decades has made a significant contribution to forest carbon storage. Vegetation carbon storage can be further increased by increasing the proportion of mature, broadleaved and state-owned forests.

Impacts of a large-scale reforestation program on carbon storage dynamics in Guangdong, China

In the early 1980s, the province of Guangdong, China implemented a 10-year, large-scale reforestation program to counter environment degradation as a result of rapid economic development. Quantification of the contribution of this forest restoration program to carbon storage will provide critical information and guidance for designing future forest restoration and management strategies at the provincial level. The Guangdong Provincial Forest Inventory Database, together with our field sampling data was used to estimate carbon storage dynamics over the 10-year period of 1994–2003 for key restoration forest types as well as OBPA (open forest, bamboo forest, production forest and ambient trees). Various layers of forests were considered in calculating carbon storage: tree layers, understory vegetation and litterfall layers for the key forest types and bamboo forests; tree layers and litterfall layers for production forests; and only tree layers for open forest and ambient trees. Our results show that over the 10-year period, the reforestation program has increased total carbon storage by 41.67 Tg and forest carbon density by 1.58 Mg C ha −1. Carbon storage in tree layers was the greatest among all layers studied. Carbon storage in litterfall and understory layers amounted to approximately 38%–44% of the total carbon storage, demonstrating that litterfall and understory layers can not be neglected in estimating regional forest vegetation carbon storage in the sub-tropical forests. It was determined that coniferous forests provided the greatest contribution to total carbon, followed by broadleaved forests, OBPA, and mixed coniferous and broadleaved forests in decreasing order of magnitude. Among all key forest types, stands of P. massoniana had the greatest amount of carbon storage (from 59.65 to 65.87Tg) while Albizia falcataria (Linn.) Fosberg forest stands had the lowest (from 0.05 to 0.37 Tg). Over the 10-year period, carbon storage pools in maturescent forests, mature forests and post-mature forests were on the increasing trend, while those in young forests and middle-aged forests were declining and relatively stable, respectively. Our analysis also shows that the carbon accumulation rate in broadleaved forests (0.19–1.36 Mg ha −1 year −1) was the highest among the key forest types in Guangdong, which has important implications for selection of future forest restoration species.

Carbon Storage of Forest Vegetation in China and its Relationship with Climatic Factors

Estimates of forest vegetation carbon storage in China varied due to different methods used in the assessments. In this paper, we estimated the forest vegetation carbon storage from the Fourth Forest Inventory Data (FFID) in China using a modified volume-derived method. Results showed that total carbon storage and mean carbon density of forest vegetation in China were 3.8 Pg C (about 1.1% of the global vegetation carbon stock) and 41.32 Mg/ha, respectively. In addition, based on linear multiple regression equation and factor analysis method, we analyzed contributions of biotic and abiotic factors (including mean forest age, mean annual temperature, annual precipitation, and altitude) to forest carbon storage. Our results indicated that forest vegetation carbon storage was more sensitive to changes of mean annual temperature than other factors, suggesting that global warming would seriously affect the forest carbon storage.