Biomass Expansion Factors Research Articles

Dynamics of carbon and CO2 removals by Brazilian forest plantations during 1990\u20132016

BackgroundWe analyzed the dynamics of carbon (C) stocks and CO2 removals by Brazilian forest plantations over the period 1990–2016. Data on the extent of forests compiled from various sources were used in the calculations. Productivities were simulated using species-specific growth and yield simulators for the main trees species planted in the country. Biomass expansion factors, root-to-shoot ratios, wood densities, and carbon fractions compiled from literature were applied. C stocks in necromass (deadwood and litter) and harvested wood products (HWP) were also included in the calculations.ResultsPlantation forests stocked 231 Mt C in 1990 increasing to 612 Mt C in 2016 due to an increase in plantation area and higher productivity of the stands during the 26-year period. Eucalyptus contributed 58% of the C stock in 1990 and 71% in 2016 due to a remarkable increase in plantation area and productivity. Pinus reduced its proportion of the carbon storage due to its low growth in area, while the other species shared less than 6% of the C stocks during the period of study. Aboveground biomass, belowground biomass and necromass shared 71, 12, and 5% of the total C stocked in plantations in 2016, respectively. HWP stocked 76 Mt C in the period, which represents 12% of the total C stocked. Carbon dioxide removals by Brazilian forest plantations during the 26-year period totaled 1669 Gt CO2-e.ConclusionsThe carbon dioxide removed by Brazilian forest plantations over the 26 years represent almost the totality of the country´s emissions from the waste sector within the same period, or from the agriculture, forestry and other land use sector in 2016. We concluded that forest plantations play an important role in mitigating GHG (greenhouse gases) emissions in Brazil. This study is helpful to improve national reporting on plantation forests and their GHG sequestration potential, and to achieve Brazil’s Nationally Determined Contribution and the Paris Agreement.

Comparison of allometric equations and biomass expansion factors for six evergreen broad-leaved trees in subtropical forests in southern Korea

ABSTRACTThis study was conducted to compare the allometric equations and biomass expansion factors (BEFs) of six dominant evergreen broad-leaved trees (Camellia japonica L, Castanopsis sieboldii Hatus, Quercus acuta Thunb, Q. glauca Thunb, Machilus thunbergii S. et Z., and Neolitsea sericea Koidz) in subtropical forests. A total of 86 trees were destructively sampled to quantify the aboveground biomass of each tree component (i.e., leaves, branches, and stem). Species-specific or generalized allometric equations and species-dependent BEFs were developed for each tree component of the six broad-leaved forest trees. Species-specific allometric equations were significant (P < 0.05), with the diameter at breast height (DBH) accounting for 68–99% of the variation, whereas generalized allometric equations explained 64–96% of the variation. The values of stem density ranged broadly from 0.49 g cm−3 for C. sieboldii to 0.79 g cm−3 for Q. glauca, with a mean value of 0.68 g cm−3. The BEFs were significantly (P < 0.05) lower for C. sieboldii (1.25) than for M. thunbergii (2.02). Stem density and aboveground BEFs had a significant negative relationship with tree ages. The results indicate that species-specific allometric equations and species-dependent BEFs are applicable for obtaining accurate biomass estimates of subtropical evergreen broad-leaved forests.

Assessing the availability of forest biomass for bioenergy by publicly available satellite imagery

Abstract: Forest biomass is a renewable energy source, more climate-friendly than fossil fuels and widely available in Europe. The wood energy chain has been suggested as a means to re-activate forest management and improve the value of forest stands in marginalized rural areas. However, wall-to-wall estimates of forest biomass, needed to design the location and size of power and heat biomass plants in any given territory, are notoriously difficult to obtain. This paper tests an algorithm to predict forest biomass using publicly available Landsat satellite imagery in the Liguria region, northern Italy. We used regional forest inventory data to train and validate an artificial neural network (ANN) classifier that uses remotely-sensed information such as three principal components of Landsat-5 TM spectral bands, the Enhanced Vegetation Index (EVI), and topography, to retrieve aboveground live tree volume. Percent root mean square error was -9% and -23% for conifers and broadleaves respectively in the calibration dataset, and -27% and -24% in the validation dataset. The reconstructed volume map was updated to present day using current volume increment rates reported by the Italian National Forest Inventory. A wall-to-wall map of forest biomass from harvest residues was finally produced based on species-specific wood density, biomass expansion factors, volume logged for timber assortments, forest accessibility, and topography. Predicted aboveground forest volume ranged from 81 to 391 m3 ha-1. In forests available for wood supply (70% of the total), planned volume removals averaged 25.4 m3 ha-1, or 18.7% of the average standing stock across. Biomass available for bioenergy supply was 1.295.921 million Mg dry matter or 8.95 Mg ha-1. This analysis workflow can be replicated in all mountain regions with a predominant broadleaved coppice component.

Biomass carbon storages and carbon sequestration potentials of the Grain for Green Program-Covered Forests in China.

The Grain for Green Program (GGP) was the most all‐embracing program of ecological reconstruction implemented in China. To estimate carbon storages and carbon sequestration potentials of the GGP forests, the study presented in the paper collected data spanning from 1999 to 2010, such as tree species, tree planting area relevant to the GGP, empirical growth curves suitable for different planted tree species in China, as well as wood density (WD), biomass expansion factor (BEF), carbon fraction (CF) of different trees species, and estimated the carbon storages of the biomasses of GGP forests from 1999 to 2050. It showed that the total carbon storage of the biomass of GGP forests was 320.29 Tg upon the GGP completion in 2010; the total carbon sequestration is higher during the early GGP‐implementation stage than at the late GGP‐implementation stage, and the annual mean carbon sequestration of GGP forests was 26.69 Tg/year. The potential of GGP forests as carbon sink presented an increasing increment. In China, the potential increments of GGP forests as carbon sinks were estimated to be 397.34, 604.00, 725.53, and 808.90 Tg in 2020, 2030, 2040, and 2050, respectively, and the carbon sequestration rates were 1.72, 0.89, 0.52, and 0.36 Mg ha−1 year−1, respectively, corresponding to 2010s, 2020s, 2030s, and 2040s. Therefore, the GGP forests had bigger carbon sequestration capacities and potentials in China.

Improved Estimates of Biomass Expansion Factors for Russian Forests

Biomass structure is an important feature of terrestrial vegetation. The parameters of forest biomass structure are important for forest monitoring, biomass modelling and the optimal utilization and management of forests. In this paper, we used the most comprehensive database of sample plots available to build a set of multi-dimensional regression models that describe the proportion of different live biomass fractions (i.e., the stem, branches, foliage, roots) of forest stands as a function of average stand age, density (relative stocking) and site quality for forests of the major tree species of northern Eurasia. Bootstrapping was used to determine the accuracy of the estimates and also provides the associated uncertainties in these estimates. The species-specific mean percentage errors were then calculated between the sample plot data and the model estimates, resulting in overall relative errors in the regression model of −0.6%, −1.0% and 11.6% for biomass conversion and expansion factor (BCEF), biomass expansion factor (BEF), and root-to-shoot ratio respectively. The equations were then applied to data obtained from the Russian State Forest Register (SFR) and a map of forest cover to produce spatially distributed estimators of biomass conversion and expansion factors and root-to-shoot ratios for Russian forests. The equations and the resulting maps can be used to convert growing stock volume to the components of both above-ground and below-ground live biomass. The new live biomass conversion factors can be used in different applications, in particular to substitute those that are currently used by Russia in national reporting to the UNFCCC (United Nations Framework Convention on Climate Change) and the FAO FRA (Food and Agriculture Organization’s Forest Resource Assessment), among others.

Allometric Relationships for Estimation of Above-Ground Biomass in Young Turkey Oak (Quercus cerris L.) Stands in Albania

Abstract The study objective was the determination of allometric relationships to estimate aboveground biomass in young Q. cerris stands growing in various sites in Albania. The equations described here are developed for Q. cerris forest stands managed as coppice. The total aboveground biomass of sampled trees varied from 10.67 to 19.71 kg with a stem diameter at 1.3 m (DBH) from 7.65 to 9.7 cm, and height from 5.26 to 7.6 m. Stem biomass comprised, on average, 69.6 %, while branch biomass was 24.3 %, and leaf biomass,6% on the total aboveground biomass of the sampled oak trees. Total aboveground biomass was predicted with the highest accuracy from linear and non-linear regression equations. Total aboveground biomass and the biomass of tree compartments were predicted with a notable accuracy from DBH where the allometric model efficiency exceeded 93%. Biomass expansion factors (BEFs) showed a stronger dependency on diameter at breast height and a weaker relationship with age. The age-dependence relationship found in our study was closely related to site productivity. The variability in aboveground biomass among sampled sites indicated that local site conditions cause this difference. These new equations for Q.cerris might be applicable in the framework of the Albanian National Forest Inventory for estimation of carbon accounting from forest ecosystems and will contribute to the sustainable management of oak forests.

The Effects of Land Cover Changes on Forest Carbon Storage in 40 Years: A Case Study in Turkey

In this study, forest biomass carbon storage changes were estimated for a case study area of Caykara planning unit based on forest inventory for the years 1971 and 2010 using tree species dependent biomass expansion factors. The outputs were handled in the context of forest dynamics represented by temporal and spatial changes of land cover. Quantitative evidence showed that there were drastic changes of carbon storage in above and below ground forest ecosystems from 2.34 Tg carbon to 3.91 Tg carbon between two periods. Carbon sequestration rate was 1.37 Mg carbon yr–1 ha–1 for living biomass due mainly to the increase of forest area and growing stock and its quality. On the other hand, such a rate of increase in carbon storage was not influenced negatively by an almost tripling in the total number of patches from 406 to 1,445 in the same period.

Biomass expansion factor of aged sugi (Cryptomeria japonica) stands in the University of Tokyo Chiba Forest

Biomass expansion factor of aged sugi (<i>Cryptomeria japonica</i>) stands in the University of Tokyo Chiba Forest

2004-2013年山东省森林碳储量及其碳汇经济价值

PDF HTML阅读 XML下载 导出引用 引用提醒 2004-2013年山东省森林碳储量及其碳汇经济价值 DOI: 10.5846/stxb201703280535 作者: 作者单位: 鲁东大学资源与环境工程学院,江苏省地理信息技术重点实验室，南京大学国际地球系统科学研究所,鲁东大学资源与环境工程学院,国家林业局林产工业规划设计院;国家林业局林产工业规划设计院,鲁东大学资源与环境工程学院 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（41601054）；山东省自然科学基金项目（ZR2016DP05，ZR2014DF004）；鲁东大学引进人才基金项目（LY2015016） Biomass carbon stocks and economic value dynamics of forests in Shandong Province from 2004 to 2013 Author: Affiliation: School of Resources and Environmental Engineering, Ludong University,Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing 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:森林作为陆地生态系统的主体，其林分碳储量及其碳汇经济价值的估算是全球碳循环研究的热点和重要内容。基于2004-2008年和2009-2013年山东省森林资源清查数据以及实测样地数据改进的生物量蓄积量转换参数，利用生物量转换因子连续函数法，估算2004-2013年山东省森林碳储量及其碳汇经济价值动态。研究结果表明，2004-2013年山东省森林面积、碳储量和碳密度分别从2004-2008年的156.12×104hm2、34.75Tg C和22.26Mg C/hm2增加到2009-2013年161.44×104hm2、43.98Tg C和27.24Mg C/hm2。人工林是森林面积、碳储量和碳密度增加的主要贡献者，人工林和天然林对森林生物量碳汇的贡献分别为97.3%和2.7%。两次森林清查期间，杨树和硬阔软阔类森林的碳储量之和分别占全省总量的70.2%和69.6%，杨树的碳储量和碳密度增加最为显著。各龄组森林碳储量由大到小依次为：幼龄林 > 中龄林 > 成熟林 > 近熟林 > 过熟林。森林碳汇经济价值从2004-2008年的243.37亿元增长到2009-2013年的253.42亿元，年均增长2.01亿元，杨树的碳汇经济价值占全省所有森林类型的60%，赤松单位面积碳汇经济价值最强为2.08万元/ha。 Abstract:Forests play an important role in global carbon sequestration and climate change mitigation strategies because they are the main component of a terrestrial ecosystem. The dynamic biomass carbon stocks and carbon sink economic value assessment of forests are important ways of assessing the global carbon cycle. Based on the forest inventory data between 2004-2008 and 2009-2013 in Shandong Province, and the updated biomass-volume relationship retrieved from field measurements, the dynamic changes of biomass carbon stocks and the economic value for Shandong's forests from 2004 to 2013 were estimated using the continuous biomass expansion factor method. The results showed that forest areas, biomass carbon stocks, and carbon density increased significantly from 156.12×104hm2, 34.75Tg C and 22.26Mg C/hm2 between 2004 and 2008 to 161.44×104hm2, 43.98Tg C and 27.24Mg C/hm2 between 2009 and 2013 in Shandong, respectively. Planted forests dominantly contributed to the increases in forest areas, biomass carbon stocks, and carbon density. About 97.3% and 2.7% of the biomass carbon sink were contributed by planted and natural forests, respectively. The biomass carbon stocks of Populus and hard broadleaf and soft broadleaf forests accounted for 70.2% of the provincial total during the period 2004-2008 and 69.6% during the period 2009-2013. Populus forests held the highest increase in biomass carbon stocks and carbon density during the study period. The magnitude of biomass carbon stocks followed the sequence young forests > middle-aged forests > mature forests > premature forests > overmature forests. The total economic value of the biomass carbon sink for Shandong's forests increased from RMB 24.337 billion yuan for the period of 2004-2008 to RMB 25.342 billion yuan for the period of 2009-2013, with the increment of RMB 0.201 billion yuan per year. The economic value of Populus forests amounted to 60% of the total for all forest types in Shandong. Pinus densiflora forests had the greatest carbon sink economic value per unit area of 2.08×104yuan/hm2. 参考文献 相似文献 引证文献

Variations in the biomass of Eucalyptus plantations at a regional scale in Southern China

We quantified deviations in regional forest biomass from simple extrapolation of plot data by the biomass expansion factor method (BEF) versus estimates obtained from a local biomass model, based on large-scale empirical field inventory sampling data. The sources and relative contributions of deviations between the two models were analyzed by the boosted regression trees method. Relative to the local model, BEF overestimated accumulative biomass by 22.12%. The predominant sources of the total deviation (70.94%) were stand-structure variables. Stand age and diameter at breast height are the major factors. Compared with biotic variables, abiotic variables had a smaller overall contribution (29.06%), with elevation and soil depth being the most important among the examined abiotic factors. Large deviations in regional forest biomass and carbon stock estimates are likely to be obtained with BEF relative to estimates based on local data. To minimize deviations, stand age and elevation should be included in regional forest-biomass estimation.

Evaluating Carbon Stock Changes in Forest and Related Uncertainty

For the evaluation of changes in the carbon stock of living biomass, two methods are reported in the Good Practice Guidance for Land Use, Land-Use Change, and Forestry: (1) the default method, which requires the biomass carbon loss to be subtracted from the biomass carbon increment for the reporting year; and (2) the stock change method, which requires two consecutive biomass carbon stock inventories for a given forest area at two points in time. We used three methods to estimate above-ground biomass: (1) application of allometric equations, (2) constant BEF (biomass expansion factor), and (3) age-dependent BEF, following which we evaluated the changes in carbon stock and the related uncertainty. Our study was carried out in a Douglas fir plantation composed of plots with three different planting densities, monitored at three different ages (15, 25, and 40 years old). Results showed the highest uncertainty in the estimates based on the constant BEF, whereas the use of allometric equations led to the lowest uncertainty in the estimates. With a constant BEF, it is usually difficult to obtain a reliable value for the whole tree biomass because stem proportion increases with tree size at the expense of the other components. The age-dependent BEFs aim to reduce the bias representing the actual change in stock, thus we found a lower uncertainty in the estimates by using this method compared to the constant BEF. The default method had the highest uncertainty (35.5–48.1%) and gave an estimate higher by almost double compared to the stock change method, which had an uncertainty ranging from 2.9% (estimated by the allometric equation) to 3.4% (estimated by the constant BEF).

Spatiotemporal Distribution and Driving Factors of Forest Biomass Carbon Storage in China: 1977–2013

Increasing forest vegetation is important for carbon dynamics and to maintain the ecological and environmental balance in China. However, there is little understanding of how socioeconomic factors affect forest biomass carbon storage (FBCS). Here, we used continuous functions for biomass expansion factors and China’s seven completed forest inventories to estimate the changes in FBCS for 31 provinces in mainland China between 1977 and 2013. We developed a model that decomposes the contribution of the different socioeconomic factors driving FBCS. We found China’s FBCS increased from 4972 TgC (1 Tg = 1012g) in 1977–1981 to 7435 TgC in 2009–2013, with a mean growth of 77 TgC/a, and the average forest carbon density increased from 36.0 to 38.9Mg/ha (1 Mg = 106g), mainly due to the arbor forest contribution. Among the seven regions in China, the southwestern region currently accounts for the highest proportion (37.3%) of national FBCS, followed by northeastern (19.7%), northern (12.5%) and eastern region (10.8%). The main socio-economic factors affecting FBCS were forest land dependence, industrial structure and economic development level. Optimizing forest type and age structure, improving forest productivity, and strengthening forest management are feasible options to further increase China’s FBCS.

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.

Revisión de métodos para el monitoreo de biomasa y carbono vegetal en ecosistemas forestales tropicales

La cuantificación de la biomasa vegetal es clave para conocer el carbono almacenado por los ecosistemas forestales y, por ende, la capacidad de mitigación del cambio climático. Existen variedad de métodos para estimar la biomasa, muchos de ellos con pequeñas variaciones, por ejemplo, el tamaño y forma de las unidades de muestreo, la inclusión o no de algún componente del reservorio (hojas, ramas, raíces, necromasa), diámetro mínimo inventariado, entre otras. El objetivo del manuscrito es explicar los aspectos más importantes a considerar en el inventario de remociones, a partir del diseño de inventario (diseño estadístico, tamaño y forma de las unidades de muestreo, componentes de la biomasa a evaluar). En un segundo punto se trata el tema de la determinación de la biomasa aérea y de raíces, haciendo referencia al método directo o destructivo y a los métodos indirectos, en especial al uso de modelos matemáticos por su fácil aplicación y bajo costo; además se anotan algunos modelos para bosque natural y plantaciones. También se hace referencia al estudio de carbono en suelos, a los factores de expansión de biomasa y a cómo determinar el carbono en la biomasa. Se espera que estas notas faciliten la comprensión del tema y que sean de referencia para el establecimiento de esquemas de monitoreo, reporte y verificación.

Biomass conversion and expansion factors in Douglas-fir stands of different planting density: variation according to individual growth and prediction equations

Aim of study: We built biomass expansion factors (BCEFs) from Douglas-fir felled trees planted with different planting densities to evaluate the differences according tree size and planting density.Area of study: The Douglas-fir plantation under study is located on the northern coastal chain of Calabria (Tyrrhenian side) south Italy.Materials and methods: We derived tree level BCEFs, relative to crown (BCEFc), to stem (BCEFst = basic density, BD) and total above-ground (BCEFt) from destructive measurements carried out in a Douglas-fir plantation where four study plots were selected according to different planting densities (from 833 to 2500 trees per hectare). The measured BCEFs were regressed against diameter at breast height and total height, planting density, site productivity (SP) and their interactions to test the variation of BCEFs. Analysis of variance (ANOVA) and the post hoc Tukey comparison test were used to test differences in BCEFt, BCEFc and in BD between plots with different planting density.Main results: BCEFs decreased with increasing total height and DBH, but large dispersion measures were obtained for any of the compartments in the analysis. An increasing trend with planting density was found for all the analyzed BCEFs, but together with planting density, BCEFs also resulted dependent upon site productivity. BCEFt average values ranged between 1.40 Mg m-3 in planting density with 833 trees/ha (PD833) to 2.09 Mg m-3 in planting density with 2500 trees/ha (PD2500), which are in the range of IPCC prescribed values for Douglas-fir trees.Research highlights: Our results showed that the application of BCEF to estimate forest biomass in stands with different planting densities should explicitly account for the effect of planting density and site productivity.

Allometric relationship and biomass expansion factors (BEFs) for above- and below-ground biomass prediction and stem volume estimation for ash (Fraxinus excelsior L.) and oak (Quercus robur L.)

Key message Complex overview of biomass structure for oak and ash tree species and wide range of allometric relationships for predicting above- and below-ground biomass components.

Estimating carbon storage and CO2 absorption by developing allometric equations for Quercus acuta in South Korea

ABSTRACTThis study was conducted to estimate C storage and CO2 absorption by developing allometric equations for Quercus acuta in South Korea. Carbon content and CO2 absorption were estimated according to climate change using data such as volume, stem density, and biomass expansion factor (BEF). Three kinds of BEFs were applied for this calculation: the national factor (NF, 1.22); the factor in this study (1.3275); and the biomass expansion regression equation (BRE) in this study. BRE among BEFs was developed to calculate BEF related to diameter at breast height (DBH) because BEF had a significantly positive relationship with DBH; the bigger DBH grew, the higher BEF increased. When applying the NF, C content and CO2 absorption were the lowest as 64.0455 t C ha−1 and 234.6840 t CO2 ha−1, respectively; whereas these were 69.6865 t C ha−1 and 255.5165 t CO2 ha−1 for the factor in this study. The highest values of C content and CO2 absorption were shown as 74.9280 t C ha−1 and 274.7365 t CO2 ha−1 when using the BRE. Carbon content prediction equations were also developed using these BEFs. Thus, BRE is suitable for developing an allometric equation for C content prediction with the greatest R2 adjusted of 0.9815.

Conversion Parameters for Stand Biomass Estimation of Four Subtropical Forests in Southern China

Even though the National Forest Resource Inventory (NFRI) does not provide detailed forest biomass information directly, the NFRI data are useful for estimating forest biomass and carbon stocks by using conversion parameters. However, the accuracy and errors of this approach for estimating the stand biomass of subtropical forests remain unclear. In this study, we selected four typical subtropical forests (Cunninghamia lanceolata plantation, Pinus massoniana evergreen coniferous forest, Choerospondias axillaris deciduous broadleaved forest, and Lithocarpus glaber–Cyclobalanopsis glauca evergreen broadleaved forest) in Dashanchong Forest Park to calculate the biomass expansion factor (BEF) and the root:shoot ratio (R). Our results showed that the average BEF values for the four forests were 1.144, 1.301, 1.592 and 1.396, respectively, while the average R values were 0.197, 0.192, 0.226 and 0.221, respectively. These results may be important for estimating forest biomass in the subtropical zone of southern China.

福建地区马尾松生物量转换和扩展因子的影响因素

福建地区马尾松生物量转换和扩展因子的影响因素

Biomass Expansion Factors Estimation of Chinese Fir (Cunninghamia Lanceolata) based on General Approach, Mixed Model Approach and Bayesian Hierarchical Approach

Biomass Expansion Factors Estimation of Chinese Fir (Cunninghamia Lanceolata) based on General Approach, Mixed Model Approach and Bayesian Hierarchical Approach