• Journal of Korean Society of Forest Science
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• v.103 no.2
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• pp.175-181
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• 2014

This study was conducted to evaluate stand density-specific and generalized allometric equations, and biomass expansion factors (BEFs) for two stand densities (high density of 47-year-old: $667tree{\cdot}ha^{-1}$; low density of 49-year-old: $267tree{\cdot}ha^{-1}$) of Cryptomeria japonica plantations in Namhae-gun, located in the southern Korea. Biomass in each tree component, i.e. foliage, branch, and stem, was quantified by destructive tree harvesting. Allometric regression equations of each tree component were significant (P<0.05) with diameter at breast height (DBH) accounting for 80-96% of the variation except for branch biomass in high density or foliage and cone biomass in low density. Generalized allometric equations can be used to estimate the biomass of C. japonica plantations because the slopes of allometric equations were not significantly different by the stand density. The biomass expansion factors (BEFs) were significantly lower in the high stand density (1.33) than in the low stand density (1.50). The results indicate that BEFs were affected by different stand density, while allometric equations were little related to the stand density.

• Journal of Korean Society of Forest Science
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• v.100 no.4
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• pp.535-539
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• 2011

This study was conducted to examine the bootstrap evaluation of the stem density and biomass expansion factor for Pinus rigida plantations in Korea. The stem density ($g/cm^3$) in less than 20 tree years were 0.460 while more than 21 tree years were 0.456 respectively. Biomass expansion factor of less than 20 years and more than 21 years were 2.013, 1.171, respectively. The results of 100 and 500 bootstrap iterations, stem density ($g/cm^3$) in less than 20 years were 0.456~0.462 while more than 21 years were 0.457~0.456 respectively. Biomass expansion factor of less than 20 years and more than 21 years were 1.990~2.039, 1.173~1.170, respectively. The mean differences between observed biomass factor and average parameter estimates showed within 5 percent differences. The split datasets of younger stands and old stands were compared to the results of bootstrap simulations. The stem density in less than 20 years of mean difference were 0.441~1.049% while more than 21years were 0.123~0.206% respectively. Biomass expansion factor in less than 20 years and more than 21 years were -1.102~1.340%, -0.024~0.215% respectively. Younger stand had relatively higher errors compared to the old stand. The results of stem density and biomass expansion factor using the bootstrap simulation method indicated approximately 1.1% and 1.4%, respectively.

• New & Renewable Energy
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• v.20 no.1
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• pp.145-174
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• 2024

Addressing climate change necessitates evidence-based policies grounded in science. The use of forest biomass for energy production is based on a broad scientific consensus at the international level. However, some environmental groups in South Korea are opposing this system of energy production. Through this study, the authors aim to reduce unnecessary confusion and foster an atmosphere conducive to meaningful evidence-based policies. We have classified the issue into eight categories: biological carbon cycle, carbon debt, nature-based solutions, air emissions, cascading principles and sustainability certification, forest environmental impacts, climate change litigation, and the behavior of environmental groups and public perception. Consequently, the following key points were derived: (1) the actions of some environmental groups seem to follow a similar pattern to denialist behavior that denies climate change and climate science; (2) the quality of evidence for campaigns that oppose the use of forest biomass for energy production is low, with a tendency to overgeneralize information, high uncertainty, and difficulty in finding new claims.; (3) most of the public believes that forest biomass energy is necessary, and the governments of major countries are aware of its importance. Significantly, Forest biomass for energy is based on an overwhelming level of scientific consensus recognized internationally.

• Journal of Ecology and Environment
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• v.44 no.4
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• pp.241-255
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• 2020

Background: The stem exclusion stage is a stage of forest development that is important for understanding the subsequent understory reinitiation stage and maturation stage during which horizontal heterogeneity is formed. Over the past 11 years (2009-2019), we observed a deciduous broad-leaved forest in the Albongbunji Basin in Ulleungdo, South Korea in its stem exclusion stage, where Fagus engleriana (Engler's beech) is the dominant species, thereby analyzing the changes in the structure (density and size distributions), function (biomass and species richness), and demographics. Results: The mean stem density data presented a bell-shaped curve with initially increasing, peaking, and subsequently decreasing trends in stem density over time, and the mean biomass data showed a sigmoidal pattern indicating that the rate of biomass accumulation slowed over time. Changes in the density and biomass of Fagus engleriana showed a similar trend to the changes in density and biomass at the community level, which is indicative of the strong influence of this species on the changing patterns of forest structure and function. Around 2015, a shift between recruitment and mortality rates was observed. Deterministic processes were the predominant cause of tree mortality in our study; however, soil deposition that began in 2017 in some of the quadrats resulted in an increase in the contribution of stochastic processes (15% in 2019) to tree mortality. The development of horizontal heterogeneity was observed in forest gaps. Conclusions: Our observations showed a dramatic shift between the recruitment and mortality rates in the stem exclusion stage, and that disturbance increases the uncertainty in forest development increases. The minor changes in species composition are likely linked to regional species pool and the limited role of the life-history strategy of species such as shade tolerance and habitat affinity. Our midterm records of ecological succession exhibited detailed demographic dynamics and contributed to the improvement of an ecological perspective in the stem exclusion stage.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.603-612
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• 2022

The study aims were to evaluate a machine-learning, algorithm-based, forest biomass-estimation model to estimate subnational forest biomass and to comparatively analyze REDD+ forest reference emission levels. Time-series Landsat satellite imagery and ESA Biomass Climate Change Initiative information were used to build a machine-learning-based biomass estimation model. The k-nearest neighbors algorithm (kNN), which is a non-parametric learning model, and the tree-based random forest (RF) model were applied to the machine-learning algorithm, and the estimated biomasses were compared with the forest reference emission levels (FREL) data, which was provided by the Paraguayan government. The root mean square error (RMSE), which was the optimum parameter of the kNN model, was 35.9, and the RMSE of the RF model was lower at 34.41, showing that the RF model was superior. As a result of separately using the FREL, kNN, and RF methods to set the reference emission levels, the gradient was set to approximately -33,000 tons, -253,000 tons, and -92,000 tons, respectively. These results showed that the machine learning-based estimation model was more suitable than the existing methods for setting reference emission levels.

• Journal of Korean Society of Forest Science
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• v.98 no.3
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• pp.311-318
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• 2009

This study purposed to construct supply and demand potential map of forest bioenergy with a GIS-based decision support system. The target areas of this study were a part of the forests in Yongdong region, Gangwondo, and most types of forests were pinus densiflora, pinus koreaiansis, and Oak. Data about forest type, age classes, the number of households, regional silviculture planning was stored in GIS to define the potential areas for supplying potential bioenergy from the forests, and to assess biomass available for a household. Theoretical potential biomass energy based on silviculture plan was estimated in average 3,144 Tcal, and this quantity will be enough to supply the quantity of demand of households in that area. However, if it assumed that average collecting rates of Kangwon province were 10%, the available quantity of biomass will be between 6% and 15% of demand. If the collecting rates were 60%, the supply of biomass could exceed the quantity of demand in certain cities.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.5
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• pp.20-30
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• 2007

Environmental Conservation Value Assessment Map (ECVAM) is the class map to divide the national land into conservation areas and development areas based on legal and ecological assessment criteria. It contributes to enhancements of the efficiency and the scientificity when framing a policy in various fields including the environment. However, it is impossible to understand the multiphase vegetation structure as data on judging the national forest class in ECVAM are restricted to areal information of Ecological Nature Status, Degree of Green Naturality and Forest Map. This point drops the reliability of ECVAM. Therefore we constructed vegetation information using LiDAR (Light Detection And Raging) technology. We generated Biomass Class Maps as final results of this study, to introduce the new forest assessment criterion in ECVAM that alternates or makes up for existing forest assessment criteria. And then, we compared these with Forest Map and Landsat TM NDVI image. As a result, biomass classes are generally higher than stand age classes and DBH classes of Vegetation Map, and lower than NDVI of Landsat TM image because of the difference of time on data construction. However distributions between these classes are mostly similar. Therefore we estimates that it is possible to apply the biomass item to the new forest assessment criterion of ECVAM. The introduction of the biomass in ECVAM makes it useful to detect the vegetation succession, to adjust the class of the changed zone since the production of Vegetation Map and to rectify the class error of Vegetation Map because variations on tree heights, forest area, gaps between trees, vegetation vitality and so on are acquired as interim findings in process of computing biomass.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.2
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• pp.206-214
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• 2011

Fifteen clones of poplars, 2 clones of willows, and yellow poplar were used to evaluate the effects of 5 treatments such as SCBLF (slurry composting and biofiltration liquid fertilizer), general slurry liquid fertilizer, chemical fertilizer, groundwater, and control (no treatment) on vitality, growth performance, and biomass production. Five cuttings for each tree species were planted in 3 replications. After planting cuttings, a coppice was induced by cutting off stems at 10cm above the ground. Data were collected for first growing season and trees were harvested at the end of October. Maximum mortality rate i.e. 96% was recorded in the cuttings treated with groundwater and minimum 92% with control (no treatment). In all tree species, sprouting of stump was not differ significantly among the treatments. Total nitrogen concentrations of leaves and stump sprouts were higher in the treatment of SCBLF than the control, 26.6% and 22.9%, respectively. Biomass production was highest in the stumps treated with chemical fertilizer, $1.98Mg\;ha^{-1}\;year^{-1}$, and lowest in control ($1.34Mg\;ha^{-1}\;year^{-1}$).

• Journal of Korean Society of Forest Science
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• v.99 no.5
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• pp.744-749
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• 2010

Enzymatic hydrolysate from non pre-treated biomass of yellow poplar (Liriodendron tulipifera) was prepared and used as resource for bioethanol production. Fresh branch (1 year old) of yellow poplar biomass was found to be a good resource for achieving high saccharification yields and bioethanol production. Chemical composition of yellow poplar varied significantly depending upon age of tree. Cellulose content in fresh branch and log (12 years old) of yellow poplar was 44.7 and 46.7% respectively. Enzymatic hydrolysis of raw biomass was carried out with commercial enzymes. Fresh branch of yellow poplar hydrolyzed more easily than log of yellow poplar tree. After 72 h of enzyme treatment the glucose concentration from Fresh branch of yellow poplar was 1.46 g/L and for the same treatment period log of yellow poplar produced 1.23 g/L of glucose. Saccharomyces cerevisiae KCTC 7296 fermented the enzyme hydrolysate to ethanol, however ethanol production was similar (~1.4 g/L) from both fresh branch and log yellow poplar hydrolysates after 96 h.

• Korean Journal of Environment and Ecology
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• v.20 no.2
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• pp.267-273
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• 2006

The biomass of Pinus densiflora stands burnt out by the 2005 Yangyang forest fire was estimated based on the grades of fire severity; light, moderate and heavy. In order to measure the post-fire ground biomass in kg/ha, the ground fuels including shrub layer were collected and weighted and the crown biomass was estimated using allometric regressions and leaf area index for dry weight of P. densiflora. The pre-fire biomass was assumed to be equal to that of non-damaged P. densiflora stands having the same characteristics. The results indicated that the forest fire burnt out fuels of stands; 3,693 kg/ha in the light-damaged, 8,724 kg/ha in the moderately-damaged, and 17,451 kg/ha in the heavily-damaged forest stands.