共查询到20条相似文献，搜索用时 609 毫秒
1.
【目的】为了探究国产高分二号(GF-2)影像在林分蓄积量估测中的潜力,并找到最佳的蓄积量估测模型。【方法】本次实验以内蒙古旺业甸林场为研究区,以高分二号卫星影像为信息源,结合2017年10月份调查的75块样地以及同时期的GF-2影像数据,提取波段特征、植被指数和纹理特征等43个遥感因子作为候选变量,利用Pearson相关系数选择出与蓄积量显著相关的6个变量,采用多元线性回归模型(MLR)、BP-神经网络模型(BP-ANN)、随机森林模型(RF)、支持向量机模型(SVM)和K邻近模型(KNN)进行蓄积量的估测。以决定系数(R^2)、均方根误差(RMSE)、相对均方根误差(RRMSE%)作为5种模型的评价指标,选择出旺业甸林场的最佳蓄积量估测模型,并绘制了研究区的森林蓄积量分布图。【结果】4种机器学习模型的结果明显优于传统的线性模型,其中随机森林(RF)模型和K邻近模型(KNN)均得到了较高的精度,其中RF模型的R^2为0.66,均方根误差为55.2 m^3/hm^2,相对均方根误差为28.1%,KNN模型的R^2为0.64,均方根误差为57.6 m^3/hm^2相对均方根误差为29.3%。【结论】在利用高分二号数据进行旺业甸林场蓄积量估测时,RF和KNN模型在估测针叶林蓄积量时相比于其他模型可以取得更好的结果。 相似文献
2.
Self-organizing maps (SOMs) are an advanced neural networks application. SOMs were applied for the spatially explicit estimation of forest carbon stocks for a test region in Thuringia (Germany). The approach utilizes in situ national forest inventory data and satellite remote sensing data (Landsat 7 ETM+) and provides maps showing a high-resolution spatial distribution of forest carbon stocks. The generated maps are compared to alternative estimates obtained by the k-nearest neighbour (kNN) method—a remote sensing based carbon assessment. Beside maps the SOM- and kNN-approaches were utilized to calculate statistical estimates of carbon stock and growing stock. The statistical estimates were validated by calculating bias and mean square errors with reference to in situ assessments. 相似文献
3.
Huiquan Bi Yushan Long John Turner Yuancai Lei Peter Snowdon Yun Li Richard Harper Ayalsew Zerihun Fabiano Ximenes 《Forest Ecology and Management》2010
A general and two country-specific systems of additive equations were developed to predict aboveground biomass of Pinus radiata plantations from stand variables that are routinely measured in inventory plots and predicted by conventional growth and yield models. The data for this work consisted of 319 plot-based biomass estimates that were derived from individual tree biomass equations developed in situ. These plot-based biomass estimates were compiled from studies reported in the forestry and ecological literature since 1960 and also from personal communications. They represent more than 60 sites worldwide with a majority in Australia and New Zealand. The systems of additive biomass equations developed from these data provide an alternative and addition to the current methods of estimating the aboveground biomass of P. radiata plantations. They also provide a direct linkage between forest inventory measures, outputs from conventional growth and yield models and biomass and carbon stock estimates at the same spatial scale. This direct linkage provides a new basis for scaling to a remote sensing image from which biomass and carbon stocks across the landscape can be mapped. Comparisons of prediction accuracies between this approach and other methods such as scaling up from individual tree biomass estimates and biomass expansion factors highlighted considerable methodological differences in the estimates of aboveground biomass and associated uncertainties over a range of stand age and conditions. These differences should be carefully evaluated before adopting a particular method to estimate aboveground biomass and carbon stocks of P. radiata plantations at a local, regional or national scale. 相似文献
4.
P.N. BeetsA.M. Brandon C.J. Goulding M.O. KimberleyT.S.H. Paul N. Searles 《Forest Ecology and Management》2011,262(6):1119-1130
The United Nations Framework Convention on Climate Change (UNFCCC) requires reporting net carbon stock changes and anthropogenic greenhouse gas emissions, including those related to forests. This paper describes the design and implementation of a nation-wide forest inventory of New Zealand’s planted post-1989 forests that arose from Land Use, Land-Use Change and Forestry activities (LULUCF) under Article 3.3 of the Kyoto Protocol. The majority of these forests are planted with Pinus radiata, with the remainder made up of other species exotic to New Zealand. At the start of the project there was no on-going national forest inventory that could be used as a basis for calculating carbon stocks and meet Good Practice Guidelines.A network of ground-based permanent sample plots was installed with airborne LiDAR (Light Detection and Ranging) for double sampling using regression estimators to predict carbon in each of the four carbon pools of above- and below-ground live biomass, dead wood and litter. Measurement, data acquisition and quality assurance/control protocols were developed specifically for the inventory, carried out in 2007 and 2008. Plots were located at the intersection of a forest with a 4 km square grid, coincident with an equivalent 8 km square grid established over the indigenous forest and “grassland with woody biomass” (Other Wooded Land). Planted tree carbon within a ground plot was calculated by an integrated system of growth, wood density and compartment allocation models utilising the data from measurements of trees and shrubs on the plots. This system, called the Forest Carbon Predictor, predicts past and future carbon in a stand and is conditioned so that the calculated basal area and mean top height equals that obtained by conventional mensuration methods at the time of the plot measurement. Mean per hectare carbon stocks were then multiplied by an estimate of the total area of post 1989 forests obtained from wall to wall mapping using a combination of satellite imagery and ortho-photography.The network of permanent samples plots and LiDAR double sampling methodology was designed to be simple and robust to change over time. In the future, using LiDAR should achieve sampling efficiencies over using ground plots alone and reduces any problems regarding restricted access on the ground. The network is to be remeasured at the end of commitment period 1, 2012, and the carbon stocks re-estimated in order to calculate change. 相似文献
5.
Estimating carbon stock in secondary forests: Decisions and uncertainties associated with allometric biomass models 总被引：1，自引：0，他引：1
Michiel van Breugel Johannes Ransijn Dylan Craven Frans BongersJefferson S. Hall 《Forest Ecology and Management》2011,262(8):1648-1657
Secondary forests are a major terrestrial carbon sink and reliable estimates of their carbon stocks are pivotal for understanding the global carbon balance and initiatives to mitigate CO2 emissions through forest management and reforestation. A common method to quantify carbon stocks in forests is the use of allometric regression models to convert forest inventory data to estimates of aboveground biomass (AGB). The use of allometric models implies decisions on the selection of extant models or the development of a local model, the predictor variables included in the selected model, and the number of trees and species for destructive biomass measurements. We assess uncertainties associated with these decisions using data from 94 secondary forest plots in central Panama and 244 harvested trees belonging to 26 locally abundant species. AGB estimates from species-specific models were used to assess relative errors of estimates from multispecies models. To reduce uncertainty in the estimation of plot AGB, including wood specific gravity (WSG) in the model was more important than the number of trees used for model fitting. However, decreasing the number of trees increased uncertainty of landscape-level AGB estimates substantially, while including WSG had limited effects on the accuracy of the landscape-level estimates. Predictions of stand and landscape AGB varied strongly among models, making model choice an important source of uncertainty. Local models provided more accurate AGB estimates than foreign models, but high variability in carbon stocks across the landscape implies that developing local models is only justified when landscape sampling is sufficiently intensive. 相似文献
6.
Cumulative losses from shifting cultivation in the tropics can affect the local to regional to global balance of carbon and nutrient cycles. We determined whether shifting cultivation in the Southern Yucatán causes feedbacks that limit future forest productivity and carbon sequestration potential. Specifically, we tested how the recovery of carbon stocks changes with each additional cultivation-fallow cycle. Live aboveground biomass, coarse woody debris, fine woody debris, forest floor litter and soil were sampled in 53 sites (39 secondary forests 2–25 years old, with one to four cultivation-fallow cycles, and 14 mature forests) along a precipitation gradient in Campeche and Quintana Roo, Mexico. From the first to the third or fourth cultivation-fallow cycle, mean carbon stocks in live aboveground biomass debris declined 64%. From the first to the third cycle, coarse woody debris declined by 85%. Despite declining inputs to soil with each cultivation-fallow cycle, soil carbon stocks did not further decline after the initial conversion from mature to secondary forest. The combined aboveground and soil carbon stock declined almost 36% after conversion from mature forest, however two additional cultivation cycles did not promote further significant decline, largely because of the stability of the soil carbon pool. Although age was the dominant factor in predicting total carbon stocks of secondary forests under shifting cultivation, the number of cultivation-fallow cycles should not be neglected. Understanding change beyond the first cycle of deforestation will enhance forest management at a local scale by improving predictions of secondary forest productivity and related agricultural productivity. A multi-cycle approach to deforestation is critical for regional and national evaluation of forest-based carbon sequestration. Finally, models of the global carbon cycle can be better constrained with more accurate quantification of carbon fluxes from land-use change. 相似文献
7.
Mikaela Schmitt-Harsh Tom P. Evans Edwin Castellanos J. C. Randolph 《Agroforestry Systems》2012,86(2):141-157
Tree removal in Latin American coffee agroforestry systems has been widespread due to complex and interacting factors that include fluctuating international markets, government-supported agricultural policies, and climate change. Despite shade tree removal and land conversion risks, there is currently no widespread policy incentive encouraging the maintenance of shade trees for the benefit of carbon sequestration. In facilitation of such incentives, an understanding of the capacity of coffee agroforests to store carbon relative to tropical forests must be developed. Drawing on ecological inventories conducted in 2007 and 2010 in the Lake Atitlán region of Guatemala, this research examines the carbon pools of smallholder coffee agroforests (CAFs) as they compare to a mixed dry forest (MDF) system. Data from 61 plots, covering a total area of 2.24 ha, was used to assess the aboveground, coarse root, and soil carbon reservoirs of the two land-use systems. Results of this research demonstrate the total carbon stocks of CAFs to range from 74.0 to 259.0 Megagrams (Mg)?C ha?1 with a mean of 127.6?±?6.6 (SE)?Mg?C ha?1. The average carbon stocks of CAFs was significantly lower than estimated for the MDF (198.7?±?32.1?Mg?C?ha?1); however, individual tree and soil pools were not significantly different suggesting that agroforest shade trees play an important role in facilitating carbon sequestration and soil conservation. This research demonstrates the need for conservation-based initiatives which recognize the carbon sequestration benefits of coffee agroforests alongside natural forest systems. 相似文献
8.
利用遥感技术获取森林特征参数来估测森林碳储量是目前的研究热点,提高森林碳储量估测技术的先进性、准确性愈加迫切。文中综合以碳卫星GOSAT、OCO-2、TANSAT作为数据源的相关研究成果,分析碳卫星数据在森林碳储量估测方面的适应性和准确性,总结各类森林碳储量研究方法的优势和不足,并针对目前存在的问题进行讨论和展望,以期为全球森林碳储量的估测及其研究提供参考。 相似文献
9.
中国林业科学研究院热带林业实验中心从2008年开始进行人工林近自然经营,为了评价经营效果对森林固碳能力的影响,以热林中心2011年、2013年、2015年对238块系统抽样样地数据为基础,采用现有的生物量方程和碳转换系数乔木林碳储量进行估算。结果表明,乔木林碳储量由2011年的605826.95t增加到2015年的721847.04t,年平均增加29005.02t,碳密度由2011年的35.94t·hm^-2增加到2015年的42.34t·hm^-2,但仍小于全国和世界的平均数。针叶林碳储量高于阔叶林,由2011年的413753.07t增加至2015年的479611.05t,年均增加16464.50t,栎类的增长幅度最大,年均增长率64.00%,碳储量最大的树种是马尾松,占总碳储量的62.92%。证明近自然经营能够有效促进森林固碳能力。 相似文献
10.
Inken Krueger Christoph Schulz Werner Borken 《European Journal of Forest Research》2017,136(1):123-137
The effect of forest conservation on the organic carbon (C) stock of temperate forest soils is hardly investigated. Coarse woody debris (CWD) represents an important C reservoir in unmanaged forests and potential source of C input to soils. Here, we compared aboveground CWD and soil C stocks at the stand level of three unmanaged and three adjacent managed forests in different geological and climatic regions of Bavaria, Germany. CWD accumulated over 40–100 years and yielded C stocks of 11 Mg C ha?1 in the unmanaged spruce forest and 23 and 30 Mg C ha?1 in the two unmanaged beech–oak forests. C stocks of the organic layer were smaller in the beech–oak forests (8 and 19 Mg C ha?1) and greater in the spruce forest (36 Mg C ha?1) than the C stock of CWD. Elevated aboveground CWD stocks did not coincide with greater C stocks in the organic layers and the mineral soils of the unmanaged forests. However, radiocarbon signatures of the O e and O a horizons differed among unmanaged and managed beech–oak forests. We attributed these differences to partly faster turnover of organic C, stimulated by greater CWD input in the unmanaged forest. Alternatively, the slower turnover of organic C in the managed forests resulted from lower litter quality following thinning or different tree species composition. Radiocarbon signatures of water-extractable dissolved organic carbon (DOC) from the top mineral soils point to CWD as potent DOC source. Our results suggest that 40–100 years of forest protection is too short to generate significant changes in C stocks and radiocarbon signatures of forest soils at the stand level. 相似文献
11.
基于TM数据的森林植物碳储量估测方法研究 总被引：4，自引：0，他引：4
以广东省第六次森林资源连续清查样地数据为基础，根据TM数据及其非线性组合的光谱信息，结合地学信息及林分信息，建立了森林植物碳储量估测的多元线性回归方程及神经网络模型。分析结果表明，神经网络模型的估测精度高于回归模型估测精度，但用它们估测落实到样地的森林植物碳储量误差仍然较大，还不能满足样地调查精度的要求。 相似文献
12.
Elham Karimzadeh Jafari Hamed Naghavi Hooman Latifi 《Journal of Sustainable Forestry》2020,39(7):750-770
ABSTRACT Background: Traditional field-based methods of measurement of biomass and carbon storage face difficulty in collecting time-consuming and expensive, suggests the use of remote sensing-based techniques. It estimates the economic value of the aboveground biomass (AGB) using satellite remote sensing across the Hyrcanian forests of Iran. Methods: The Landsat-8 OLI sensor data were combined with field-based allometric information of 186 circular sample plots. The AGB was calculated at the plot level using the collected data and specific volumetric mass for species in the studied area. It was followed by calculating the carbon storage using a 50% carbon coefficient and the photosynthesis equation at the forest parcel level. Model results using the random forest and support vector machines. The carbon sequestration value was calculated with USD 25.3 as a shadow value of carbon in 2014 and using the replacement cost approach. Results: The highest performances achieved by RF for biomass, carbon storage and the carbon storage value (Iranian Rials of 0.67% and 16%, respectively). The value was derived once at the plot level of 12.22 million IRR (370.43 USD) per ha. In addition, at the parcel level, which resulted in an estimated value of 12.87 million IRR (390.24 USD) per ha. 相似文献
13.
Nicolas Latte Gilles Colinet Adeline Fayolle Philippe Lejeune Jacques Hébert Hugues Claessens Sébastien Bauwens 《European Journal of Forest Research》2013,132(4):565-577
Forest ecosystems play a major role in atmospheric carbon sequestration and emission. Comparable organic carbon stock estimates at temporal and spatial scales for all forest pools are needed for scientific investigations and political purposes. Therefore, we developed a new carbon stock (CS) estimation procedure that combines forest inventory and soil and litter geodatabases at a regional scale (southern Belgium). This procedure can be implemented in other regions and countries on condition that available external carbon soil and litter data can be linked to forest inventory plots. The presented procedure includes a specific CS estimation method for each of the following forest pools and subpools (in brackets): living biomass (aboveground and belowground), deadwood (dead trees and snags, coarse woody debris and stumps), litter, and soil. The total CS of the forest was estimated at 86 Tg (185 Mg ha?1). Soil up to 0.2 m depth, living biomass, litter, and deadwood CSs account, respectively, for 48, 47, 4, and 1 % of the total CS. The analysis of the CS variation within the pools across ecoregions and forest types revealed in particular that: (1) the living biomass CS of broadleaved forests exceeds that of coniferous forests, (2) the soil and litter CSs of coniferous forest exceed those of broadleaved forests, and (3) beech stands come at the top in carbon stocking capacity. Because our estimates differ sometimes significantly from the previous studies, we compared different methods and their impacts on the estimates. We demonstrated that estimates may vary highly, from ?16 to +12 %, depending on the selected methods. Methodological choices are thus essential especially for estimating CO2 fluxes by the stock change approach. The sources of error and the accuracy of the estimates were discussed extensively. 相似文献
14.
Durai Sanjay Gandhi 《Journal of Sustainable Forestry》2017,36(4):358-374
Climate change and carbon mitigation through forest ecosystems are some of the important topics in global perspective. Tropical dry forests are one of the most widely distributed ecosystems in tropics, which remain neglected in research. The soil organic carbon (SOC) stock was quantified on a large scale (30 1-ha plots) in the dry deciduous forest of the Sathanur reserve forest of Eastern Ghats. The SOC stock ranged from 16.92 to 44.65 Mg/ha with a mean value of 28.26 ± 1.35 Mg/ha. SOC exhibited a negative trend with an increase in soil depth. A significant positive correlation was obtained between SOC stocks and vegetation characteristics viz. tree density, shrub basal area, and herb species richness, while a significant negative correlation was observed with bulk density. The variation in SOC stock among the plots obtained in the present study could be due to differences in tree abundance, herb species richness, shrub basal area, soil pH, soil bulk density, soil texture etc. The present study generates a large-scale baseline data of dry deciduous forest SOC stock, which would facilitate SOC stock assessment at the national level as well as to understand its contribution on a global scale. 相似文献
15.
Estimation of accurate biomass of different forest components is important to estimate their contribution to total carbon stock. There is lack of allometric equations for biomass estimation of woody species at sapling stage in tropical dry forest (TDF), and therefore, the carbon stored in this forest component is ignored. We harvested 46 woody species at sapling stage in a TDF and developed regression models for the biomass estimation of foliage, branch, bole and the total aboveground part. For foliage and branch biomass, the models with only stem diameter as estimator showed greater R 2. For bole and aboveground biomass, the models including wood specific gravity or wood density exhibited higher R 2 than those without wood density. Also, the model consisting of wood density, stem diameter and height had the lowest standard error of estimate for bole and aboveground biomass. Moreover, the R 2 values are very similar among models for each component. The measurement error of height and the use of a standard value of wood density together may introduce more than 2 % error into the models. Therefore, we suggest using diameter-only model, which may be more practical and equally accurate when applied to stands outside our study area. 相似文献
16.
油松人工林碳汇功能的研究 总被引：2，自引：0，他引：2
对木兰林管局油松人工林19块标准地分林木层、灌木层、草本植物层、枯落物层和土壤层进行了生物现存量的实测与碳储量的研究,结果表明林木层和土壤层的碳储量构成了林分碳储量的主体.分配次序为土壤层＞林木层＞地表枯落物层＞草本层＞根桩＞灌木层,林木层碳储量分配次序为干＞枝＞根＞叶.建立了林木蓄积与生物量、碳储量的回归模型,认为幂函数形式有较好的适用性.以林龄(A)和3株优势木平均高(H)建立了土壤有机碳密度(Soc)拟合方程,可用于具体小班土壤碳密度的估测.木兰林管局油松人工林林分碳密度为76.586 2～284.417 8t/hm2,平均值为143.1 t/hm2,其中林木平均碳密度为30.454 5t/hm2,土壤平均碳密度为110.773 5t/hm2;现有油松人工林碳储量估测结果为983 314.0 t,其中林木碳储量为208 923.0 t,占总碳储量的21.25%,土壤碳储量为760 881.0 t,占总碳储量的77.38%. 相似文献
17.
Land-use changes and land cover strongly influence carbon stock and distribution within ecosystems. Changing the land-use from natural forest to other land-uses has been more rapid in the past few decades than at any time in Iran’s history. In this study, we investigated the effects of changing the land-use from natural forest to other land-uses on carbon stocks in northern Iran. We selected five sites for this study: (I) a natural forest, (II) an agricultural field and (III) plantations of three different species (Alnus subcordata. L, Acer velutinum.Boiss and Cupressus sempervirens). We examined the effects of land-use changes on: (I) soil carbon stock (0–50 cm depth), (II) biomass and carbon content of grassy vegetation and litter and (III) above- and below-ground biomass C in trees. Soil C stock was higher under A. velutinum and C. sempervirens whereas it was lower under A. subcordata and agricultural sites. Biomass and C content of grassy vegetation were significantly higher at A. velutinum and C. sempervirens plantations. However, litter biomass and C content were significantly higher at the natural forest site. Natural forest had the highest amount of C content in above- and below-ground biomass. Total ecosystem C stocks declined following land-use changes. 相似文献
18.
森林的碳汇功能对缓解气候变化具有重要作用, 森林碳汇的计量和监测方法备受关注, 其中应用遥感方法对森林地上部分碳汇进行监测计量已经成为目前林业遥感的热点。文中基于光学遥感、微波雷达和激光雷达3种常用的遥感数据源综述了国外森林地上部分碳汇遥感监测的主要方法, 并讨论了这些监测方法的精度和不确定性。得出:1)基于光学遥感数据的多元回归分析法在森林地上部分碳汇估算中应用最为广泛, 人工神经网络法具有更高的估算精度; 2)微波雷达系统能够穿透云层, 可用于多云地区森林地上部分碳汇的估算; 3)基于激光雷达数据的估算结果是三者中精度最高的, 可用于高生物量地区森林地上部分碳汇的监测。 相似文献
19.
Mapping and spatial uncertainty analysis of forest vegetation carbon by combining national forest inventory data and satellite images 总被引：3，自引：0，他引：3
Guangxing Wang Tonny Oyana Maozhen Zhang Samuel Adu-Prah Siqi Zeng Hui Lin Jiyun Se 《Forest Ecology and Management》2009,258(7):1275-1283
Forests play an important role in carbon sinks and mitigation of atmospheric concentrations of carbon dioxide and greenhouse effect. Given that sample plots used for collection of forest carbon observations are often much smaller than the map units of forest carbon at regional, national, and global scales, scientists are currently experiencing two challenges. The first challenge is to produce reliable maps of forest carbon using the data from inconsistent sizes of plots and image pixels. Also, because estimates of forest carbon normally contain uncertainties, the second challenge is to accurately model propagation of uncertainties from input data to output results. In this study, a methodology for mapping and analyzing spatial uncertainty of forest carbon estimates was developed to address these challenges. The methodological framework consisted of two methods. The first one was up-scaling method that combined and scaled up existing national forest inventory plot data and satellite images from smaller sample plots and image pixels to larger map units. The second one was spatial uncertainty analysis and error budget method that entailed modeling propagated uncertainties through a geostatistical mapping system. A case study using 46 permanent national forest inventory plots from Wu-Yuan County, Jiangxi, China, was undertaken to test this methodology. The results showed that this method reproduced not only the spatial distribution of forest carbon but also the spatial pattern of variances of its estimates and was able to quantify the contributions of uncertainties from the field plot data and satellite images to the uncertainties of forest carbon estimates. Thus, this study, to some extent, overcame the gaps that currently exist in the generation and assessment of forest carbon estimation maps. Moreover, the results showed that in this case study, the variation of the band ratio defined as (TM2 + TM3 + TM5)/TM7 contributed more uncertainties to the estimates of forest carbon than the variation of the plot data. In addition, we also found out that the product of the input plot forest carbon variance and the band ratio variance, implying the interaction between these two variables, reduced the uncertainties of the forest carbon estimates. 相似文献
20.
César Pérez-Cruzado Godefridus M. J. Mohren Agustín Merino Roque Rodríguez-Soalleiro 《European Journal of Forest Research》2012,131(6):1695-1716
Although it is known that forestry mitigates carbon emissions to some degree, there is still a need to investigate the extent to which changes in forest management regimes affect the carbon cycle. In a climate-change scenario, forest management schemes must be optimized to maximize product supply and minimize environmental impacts. It is difficult to predict the mitigating effects of different silvicultural regimes because of differences in the growth characteristics of each species, destination of products, and industrial efficiencies. The objective of the present study was to use a modeling approach to evaluate the effects of different management regimes for fast growing species in southern temperate Europe in relation to mitigating climate change. A comprehensive study was carried out considering the C sink effect in biomass, soil and wood products, the substitutive effect of bioenergy, and particular conditions of the forest industry in southern Europe. The mechanistic CO2Fix model was parameterized for three species used in fast growing plantations in southern Europe: Eucalyptus globulus, Eucalyptus nitens, and Pinus radiata. Data from 120 plots covering the complete age range observed for each species were used to calculate changes in C stocks in aboveground biomass and organic and mineral soil and to validate the parameterized model for these conditions. Additional information about the efficiency of forest industry processes in the region was also considered. A strong bias in soil organic carbon estimation was observed and attributed to overestimations in the decomposition rates of soil compartments. Slight bias was also observed in the carbon biomass estimation when forest-specific yield models were used to simulate afforestation over former pastureland. As regards the model sensitivity, the Yasso model was strongly robust to turnover of leaves, roots, and branches. The chip wood production alternative yielded higher carbon stock in biomass and products, as well as in bioenergy substitution effect, than the sawn wood production alternative. Nevertheless, the sawn wood alternative was the most effective as regards the C stock in the soil. Site index had an important effect for all species, alternatives, and compartments, and mitigating effects increased with site index. Harvesting of clearcutting and thinning slash for bioenergy use led to a slight decrease in the soil carbon equilibrium but significantly increased the mitigation effect through bioenergy use. 相似文献