• Journal of Climate Change Research
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• v.8 no.4
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• pp.385-391
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• 2017

This study was conducted to estimate litter carbon stock change from the National Forest Inventory (NFI) data for national greenhouse gas inventory report. Litter carbon stocks were calculated from the NFI dataset in NFI5 (2008) and NFI6 (2013) in Gangwon province. Total carbon stock change of litter was $0.68{\pm}0.71\;t\;C/ha$ from NFI5 (2008) to NFI6 (2013), however, there was no significant difference between the both dataset at 2008 and 2013 year. Litter carbon stock of coniferous stands was higher than deciduous stands in NFI5 (2008) and NFI6 (2013) (P<0.05). This study was limited to pilot study, so we will assess litter carbon stock using more complete data from NFI systems. It can be used as data sources for national greenhouse gas inventory report on forest sector.

• Journal of Forest and Environmental Science
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• v.33 no.1
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• pp.39-48
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• 2017

With the growing global concern about climate change, relationship between carbon stock density and tree species has become important for international climate change mitigation programmes. In this study, 150 Quadrats were laid down to assess the diversity, biomass and carbon stocks in each of the forest ranges (Barkot Range, Lachchiwala Range and Thano Range) of Dehra Dun Forest Division in Doon Valley, Western Himalaya, India. Community level carbon stock density was analyzed using Two Way Indicator Species Analysis. Species Richness and Shannon Weiner index was correlated with the carbon stocks of Doon Valley. Positive and weak relationship was found between the carbon stock density and Shannon Weiner Index, and between carbon stock density and Species Richness.

• Journal of Forest and Environmental Science
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• v.34 no.2
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• pp.145-152
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• 2018

Quantification of Carbon stock has become in the contest of changing climate and mitigation potential of forests. Two different forest types, Dry Shiwalik Sal Forest and Moist Shiwalik Sal Forest in Barkot and Lachchiwala of Doon Valley, Western Himalaya are selected for the study. Volume equations, destructive sampling and laboratory analysis are done to estimate the carbon stock in different carbon pools like trees, shrubs, herbs and soils. Considerable variations are observed in terms of carbon stocks in different forest types. In Dry Shiwalik Sal Forest, carbon stock density varied between 129.81 and $136.00MgCha^{-1}$ while in Moist Shiwalik Sal Forest, carbon stock density ranged from 222.29 to $271.67MgCha^{-1}$. Tree species like Shorea robusta, Syzigium cumini, Miliusa velutina, Acacia catechu, and Mallotus philippensis had significant role in carbon sequestration. Shorea robusta had contributed highest in carbon stock due to highest density. Total of 2,338,280.165 Mg carbon stock was estimated in all the forest types.

• Journal of Korean Society of Rural Planning
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• v.21 no.4
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• pp.27-33
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• 2015

Forest ecosystem is considered as an important stepping stone to minimize the impact of climate change. However, the rapid urbanization has caused fragmentation of forest ecosystem. The fragmentation of forest patch results in edge effect which brings about adverse impacts on forest function and structure. Degradation of forest ecosystem decreases carbon sequestration because edge effect reduces productivity. Therefore, we analyzed the impact of forest edge effect on forest ecosystem carbon stock change in Seongnam-si, Gyeonggi-do. We used connectivity analysis to determine forest edge and core area. The field study sites were selected with considering forest age, density, class and soil type. Secondly, forest carbon stock was calculated with allometric equation. The soil carbon stock was derived from Walkely-Black method. Lastly, Mann-Whitney test was conducted to validate differences between carbon stock in edge and core area. As a result of study, the connectivity analysis was effective to determine forest edge and core. The core and edge of forest patch showed different composition of tree species and soil properties. Carbon stock per tree in the edge area was lower than that in the core area. However, the difference of soil organic carbon content between the edge and core were relatively small. This assessment can be applied for the conservation of forest patch as well as quantitative assessment on the forest carbon stock change caused by fragmentation.

• Journal of Forest and Environmental Science
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• v.36 no.1
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• pp.37-46
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• 2020

Vegetation carbon sequestration and regeneration are the two major parameters of forest research. In this study, we analyzed the vegetation carbon stock and regeneration of community-managed pine plantation of Kathmandu, central Nepal. Vegetation data were collected from 40 circular plots of 10 m radius (for the tree) and 1m radius (for seedling) applying a stratified random sampling and nested quadrat method. The carbon stock was estimated by Chave allometric model and estimated carbon stock was converted into CO₂ equivalents. Density-diameter (d-d) curve was also prepared to check the regeneration status and stability of the plantation. A d-d curve indicates the good regeneration status of the forest with a stable population in each size class. Diversity of trees was very low, only two tree species Pinus roxburghii and Eucalyptus citriodora occurred in the sample plots. Pine was the dominant tree in terms of density, basal area, biomass, carbon stock and CO₂ stock than the eucalyptus. The basal area, carbon stock and CO₂ stock of forest was 33±1.0 ㎡ ha^-1, 108±5.0 Mg ha^-1 and 394±18 Mg ha^-1, respectively. Seedling and tree density of the plantation was 4,965 ha^-1 and 339 ha^-1 respectively. The forest carbon stock showed a positive relationship with biomass, tree diameter, height and basal area but no relationship with tree density. Canopy cover and tree diameter have a negative effect on seedling density and regeneration. In conclusion, the community forest has a stable population in each size class, sequestering a significant amount of carbon and CO₂ emitted from densely populated Kathmandu metro city as the forest biomass hence have a potentiality to mitigate the global climate change.

• Journal of Climate Change Research
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• v.6 no.4
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• pp.303-310
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• 2015

This study was conducted to estimate of carbon stock and greenhouse gas (GHGs) removals by tree species and forest type at Gangwon province. We used a point sampling data with permanent sample plots in national forest inventory and national emission factors. GHGs emissions was caclulated using the stock change method related to K-MRV and IPCC guidance. Total carbon stock and greenhouse gas removals were high in deciduous forest and species than in coniferous. The range of annual net greenhouse gas emissions in other deciduous species was from $-11,564.83Gg\;CO_2\;yr^{-1}$ to $-13,500.60Gg\;CO_2\;yr^{-1}$ during 3 years (2011~2013). On the other hand, coniferous forest was temporally converted to source due to reducing of growing stock in 2012. It was that growing stocks and forest area were likely to reduce by the deforestation and clear cutting. This study did not consider other carbon pools (soil and dead organic matter) due to the lack of data. This study needs to complement the activity data and emission factors, and then will find the way to calculate the greenhouse gas emissions and removals in the near future.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.1097-1107
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• 2020

Assessment of soil carbon stock is essential for climate change mitigation and soil fertility. The digital soil mapping (DSM) is well known as a general technique to estimate the soil carbon stocks and upgrade previous soil maps. The aim of this study is to calculate the soil carbon stock in the top soil layer (0 to 30 cm) in Jeolla Province of South Korea using the DSM technique. To predict spatial carbon stock, we used Cubist, which a data-mining algorithm model base on tree regression. Soil samples (130 in total) were collected from three depths (0 to 10 cm, 10 to 20 cm, 20 to 30 cm) considering spatial distribution in Jeolla Province. These data were randomly divided into two sets for model calibration (70%) and validation (30%). The results showed that clay content, topographic wetness index (TWI), and digital elevation model (DEM) were the most important environmental covariate predictors of soil carbon stock. The predicted average soil carbon density was 3.88 kg·m-2. The R2 value representing the model's performance was 0.6, which was relatively high compared to a previous study. The total soil carbon stocks at a depth of 0 to 30 cm in Jeolla Province were estimated to be about 81 megatons.

• Journal of Forest and Environmental Science
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• v.37 no.3
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• pp.193-205
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• 2021

The importance of forests and trees in climate change mitigation and soil nutrient cycling cannot be overemphasized. This study assessed the above-ground carbon stock of two exotic and two indigenous tree species - Gmelina arborea, Tectona grandis, Khaya grandifoliola and Nauclea diderrichii and their litter impact on soil nutrient content of an arboretum within the University of Port Harcourt, Nigeria. Data were collected from equal sample plots from the four species' compartments. Tree growth variables including total height, diameter at breast height, crown height, crown diameter and merchantable height were measured for the estimation of above-ground carbon stock. Soil samples were collected from a depth of 0-30 cm from each compartment and analyzed for particle size distribution, organic carbon, total nitrogen, available phosphorus, exchangeable bases, exchangeable acidity, cation exchange capacity, base saturation, pH, Manganese, Iron, Copper and Zinc. Analysis of Variance (ANOVA) was used to test for significant difference (p<0.05) in the carbon contents of the four species and the soil nutrient contents of the different species' compartments. Pearson correlation was used to assess the relationships between the carbon contents, growth parameters and soil parameters. The highest and lowest carbon stock per hectare was observed for G. arborea (151.52 t.ha^-1) and K. grandifoliola (45.45 t.ha^-1) respectively. Cation exchange capacity and base saturation were highest and lowest for soil under G. arborea and K. grandifoliola respectively. The pH was highest and lowest for soil under G. arborea and T. grandis respectively. Carbon stock correlated positively with dbh, crown diameter, merchantable height and Zn and negatively with base saturation. The study revealed that G. arborea and N. diderrichii can effectively be used for reforestation and afforestation programmes aimed at climate change mitigation across Nigeria. Therefore, policies to encourage and enhance their planting should be encouraged.

• Journal of Forest and Environmental Science
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• v.33 no.4
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• pp.281-294
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• 2017

Tropical forests constitute almost half of the global forest cover, account for 35% of the global net primary productivity and thereby have potential to contribute substantially to sequester atmospheric $CO_2$ and offset climate change impact. However, deforestation and degradation lead by unsustainable management of tropical forests contribute to the unprecedented species losses and limit ecosystem services including carbon sequestration. Sustainable forest management (SFM) in the tropics may tackle and rectify such deleterious impacts of anthropogenic disturbances and climatic changes. However, the existing dilemma on the definition of SFM and lack of understanding of how tropical forest sustainability can be achieved lead to increasing debate on whether climate change mitigation initiatives would be successful. We reviewed the available literature with a view to clarify the concept of sustainability and provide with a framework towards the sustainability of tropical forests for enhanced carbon stock and climate change mitigation. We argue that along with securing forest tenure and thereby reducing deforestation, application of reduced impact logging (RIL) and appropriate silvicultural system can enhance tropical forest carbon stock and help mitigate climate change.

• Journal of Climate Change Research
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• v.7 no.2
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• pp.137-142
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• 2016

To achieve large-scale carbon removals, a carbon offset project based on forest management was designed and its carbon stock change was estimated in this study. The project was designed for 874 hectares of forests in the Jin-An Leading Forest Management Zone. For estimating the carbon stock change of the project, the Korean Forest Carbon Standard and VCS (Verified Carbon Standard) methodologies were applied. Three types of management options were considered in the project : extension of rotation age, conversion to productive forests, and conversion to selective harvesting. The estimated carbon removals from the project designed in this study were $259,936tCO_2$ ($8,664tCO_2$ annually), which is 98% of estimated carbon removals from the entire 69 projects currently registered to the Forest Carbon Offset Registry in Korea. The results of this study showed that a large-scale carbon offset project based on forest management could have a huge potential to produce carbon offset credits.