Yeong Mo Son

Carbon and nitrogen storage in an age-sequence of Pinus densiflora stands in Korea

The carbon (C) and nitrogen (N) storage capabilities of Pinus densiflora in six different stand ages (10, 27, 30, 32, 44, and 71 years old) were investigated in Korea. Thirty sample trees were destructively harvested and 12 were excavated. Samples from the above and belowground tree components, coarse woody debris (CWD), forest floor, and mineral soil (0–30 cm) were collected. Tree biomass was highest in the 71-year-old stand (202.8 t ha−1) and lowest in the 10-year-old stand (18.4 t ha−1). C and N storage in the mineral soil was higher in the 71-year-old stand than in the other stands, mainly due to higher soil C and N concentrations. Consequently, the total ecosystem C and N storage (tree+forest floor+CWD+soil) was positively correlated with stand age: increasing from a minimum in the 10 year old stand (18.8 t C ha−1 and 1.3 t N ha−1) to a maximum in the 71-year-old stand (201.4 t C ha−1 and 8.5 t N ha−1). The total ecosystem C storage showed a similar sigmoidal pattern to that of tree C storage as a function of the age-sequence, while N storage in the CWD, forest floor and mineral soil showed no significant temporal trends. Our results provide important insights that will increase our understanding of C and N storage in P. densiflora stands and our ability to predict changes according to stand age in the region.

Biomass accumulations and the distribution of nitrogen and phosphorus within threeQuercus acutissima stands in central Korea

Above- and belowground biomass and nitrogen (N) and phosphorus (P) distribution within threeQuercus acutissima stands were investigated in central Korea. The average age (year) and diameter at breast height (DBH, cm) were 10.8 and 7.9 for Stand 1, 38.2 and 17.1 for Stand 2, and 44.0 and 20.7 for Stand 3, respectively. Fifteen trees were destructively harvested for dimension analysis of component biomass (stem wood, stem bark, foliage, branches, and roots) plus N and P concentrations. Total biomass (t ha-1) was 88.7 for Stand 1, 154.9 for Stand 2, and 278.1 for Stand 3 while N and P contents in all tree components (kg ha-1) were 483.3 and 52.2, 697.1 and 55.0, and 1113.9 and 83.7. Nitrogen concentrations were highest in the foliage, followed by the stem bark, branches or roots, and stem wood. In contrast, P concentrations were greatest in the roots, then foliage, branches, stem bark, and stem wood. In general, N and P concentrations in these components significantly decreased with tree age and DBH, while N and P contents significantly increased with age and size. These relationships were stronger for size than for age. Our current data could be utilized to estimate N and P budgets for silvicultural practices, including fertilization, thinning, and harvesting.

Influence of stand age class on biomass expansion factor and allometric equations for Pinus rigida plantations in South Korea

Abstract The objective of this study was to examine the influence of stand age class (I:<20 years old; II: 21–40 years old; III: 41–60 years old) on BEF and stem density and to develop allometric equations for the three stand age classes in order to estimate the biomass of pitch pine (Pinus rigida Mill.) plantations in South Korea. BEFs (g g−1) were observed to decrease in the three stand age classes with 1.983 for stand I, 1.201 for stand II and 1.131 for stand III. Results showed that there was a significant statistical difference in BEFs (p < 0.05) among the stand age classes. The stem densities (g cm−3) of the three stands were 0.430, 0.451 and 0.481, respectively, and there was no significant statistical difference (p > 0.05) among stand age classes. Both model 1 (DBH as predictor variable) and model 2 (DBH and total height as predictor variables) showed good results based on the model evaluation criteria (R 2 , RMSE and FI). The stem wood had the highest biomass distribution percentage of the three age classes with 52%, 67% and 69% determined for classes I, II and III, respectively. Stand age-dependent BEFs and allometric equations will help forest managers to accurately estimate the biomass and carbon stocks of the different pitch pine plantations in South Korea, which is essential in climate change mitigation.

Biomass and carbon storage in an age-sequence of Japanese red pine (Pinus densiflora) forests in central Korea

The biomass and carbon (C) storage of the main ecosystem components were examined in an age-sequence of six Japanese red pine forest stands in central Korea. The tree biomass was determined by the destructive method, and the C storage of the tree biomass, forest floor and mineral soil was estimated by analyzing the C concentration of each component. The above-ground and total tree biomass increased from 21.76 and 28.82 Mg ha−1 in the 17-year-old stand to 308.83 and 385.74 Mg ha−1 in the 73-year-old stand. The comparisons of above-ground tree and tree root biomass in replicate stands indicated that stand density has an effect on tree biomass partitioning for Japanese red pine, especially on the biomass allocation of above-ground tree and tree roots. The C concentrations were lowest in the tree roots while the highest concentrations were found in the foliage across the six Japanese red pine forest stands. The C storage in the forest floor and mineral soil were age-independent. The above-ground and total ecosystem C stocks increased from 19.40 and 43.49 Mg ha−1 in the 17-year-old stand to 162.72 and 247.39 Mg ha−1 in the 73-year-old stand. Although the total tree biomass C showed considerable accumulation with stand age, the relative contribution of the below-ground ecosystem to the total ecosystem C storage demonstrated large variation. The results of this study assist in understanding C storage and its change with stand development in Japanese red pine forests, which makes this species a large sink for atmospheric C at the regional scale.

Estimating the Changes in Forest Carbon Dynamics of Pinus densiflora and Quercus variabilis Forests in South Korea under the RCP 8.5 Climate Change Scenario

Forests contain a huge amount of carbon (C) and climate change could affect forest C dynamics. This study was conducted to predict the C dynamics of Pinus densiflora and Quercus variabilis forests, which are the most dominant needleleaf and broadleaf forests in Korea, using the Korean Forest Soil Carbon (KFSC) model under the two climate change scenarios (2012−2100; Constant Temperature (CT) scenario and Representative Concentration Pathway (RCP) 8.5 scenario). To construct simulation unit, the forest land areas for those two species in the 5th National Forest Inventory (NFI) data were sorted by administrative district and stand age class. The C pools were initialized at 2012, and any disturbance was not considered during the simulation period. Although the forest C stocks of two species generally increased over time, the forest C stocks under the RCP 8.5 scenario were less than those stocks under the CT scenario. The C stocks of P. densiflora forests increased from 260.4 Tg C in 2012 to 395.3 (CT scenario) or 384.1 Tg C (RCP 8.5 scenario) in 2100. For Q. variabilis forests, the C stocks increased from 124.4 Tg C in 2012 to 219.5 (CT scenario) or 204.7 (RCP 8.5 scenario) Tg C in 2100. Compared to 5th NFI data, the initial value of C stocks in dead organic matter C pools seemed valid. Accordingly, the annual C sequestration rates of the two species over the simulation period under the RCP 8.5 scenario (65.8 and 164.2 g C m yr for P. densiflora and Q. variabilis) were lower than those values under the CT scenario (71.1 and 193.5 g C m yr for P. densiflora and Q. variabilis). We concluded that the C sequestration potential of P. densiflora and Q. variabilis forests could be decreased by climate change. Although there were uncertainties from parameters and model structure, this study could contribute to elucidating the C dynamics of South Korean forests in future.

Estimating the age-dependent changes in carbon stocks of Scots pine (Pinus sylvestris L.) stands in Turkey

Abstract• Key messageSimulated and observed carbon stocks in Scots pine forests varied considerably with stand age. The contribution of biomass to the total forest carbon stocks increased and that of dead organic matter decreased with increasing stand age.• Context Understanding changes in forest carbon stocks over time is important to estimate carbon inventory. Although Scots pine (Pinus sylvestris L.) is a main species in Turkey, studies on such changes are still lacking.• Aims We aimed to estimate the changes in carbon stocks, with stand age, of Scots pine stands in Turkey using field work data and a forest carbon model (FBDC model).• Methods Biomass and dead organic matter carbon stocks were investigated to adjust the forest carbon model and to verify the model estimates. Forest carbon stocks with regards to stand age were simulated.• Results The simulated carbon stocks were generally in clear agreement with the observed values on a stand scale. Changes in simulated and observed carbon stocks of biomass and dead organic matter varied with stand age. The contribution of biomass to total forest carbon stocks increased, and that of dead organic matter decreased, with increasing stand age.• Conclusion We found that the carbon stocks in each pool and their contribution to the total forest carbon stocks varied with stand age. Our results are expected to contribute to the understanding of annual changes in the carbon stocks of Turkish forests.

DBH-height modeling and validation for Acacia mangium and Eucalyptus pellita in Korintiga Hutani Plantation, Kalimantan, Indonesia

Diameter at breast height (DBH)-height models were developed and validated for Acacia mangium and Eucalyptus pellita species in the tree plantation of Pangkalan Bun, central Kalimantan, Indonesia, using the six commonly used nonlinear growth models. A total of 2992 and 4511 total height and DBH measurements were used for A. mangium and E. pellita species, respectively. These data were randomly split into two datasets. The majority of the data (80%) were used for the initial model development and the remaining data (20%) were applied for model validation. The combined data (100%) were used for the final model development. For model validation, the bias () for each DBH class (5 cm interval) and the overall bias were determined. The performance of the developed models were evaluated and ranked using the coefficient of determination (R2), root mean square error (RMSE), bias, absolute mean difference (AMD) and Furnival index (FI). The Weibull model had the best performance followed by the Chapman-Richards model in predicting the total height of A. mangium species and for E. pellita, the Korf/Lundqvist and Chapman-Richards models were the best models based on the evaluation statistics and rank analysis.

Estimation of the Greenhouse Gas Inventory on Forest Land at Provincial Level

This study was conducted to estimate of the greenhouse gas inventory on forest land at provincial level. The greenhouse gas emissions are calculated according to the K-MRV guidance. We collected activity data from statistical yearbook of forestry and used default emission factors. The annual total CO2 emission in forest land was -58,711 Gg CO2eq. and the annual CO2 emission in loss such as fellings, fuelwood and fire was 19,896 Gg CO2eq. in 2011. The results showed the removals of carbon dioxide in the forest land, it’s amount was -38,815Gg CO2eq. in 2011. Annual net CO2 removal of local forest was highest in Kangwon province in 2011. Our study did not use the many statistics due to exclusion of double counting. There are need complementary activity data and emission factors, and then we will find a way to calculate the greenhouse gas emissions/removals in the near future.

Height-age model and site index curves for Acacia mangium and Eucalyptus pellita in Indonesia

ABSTRACT Height-age growth models and site index curves were developed for the site quality evaluation of Acacia mangium Willd and Eucalyptus pellita F. Muel stands in Korintiga Hutani plantation, Pangkalan Bun, Central Kalimantan, Indonesia. In this study, the Chapman-Richards growth function was used in the guide curve method to generate anamorphic site index curves for the two species. In order to evaluate the developed models, coefficient of determination (R2), root mean square error (RMSE), bias (), absolute mean difference (AMD), and mean percent bias (MPB) were used as statistical criteria. In addition, a simple linear regression and simultaneous F-test was performed to evaluate the relationship of the observed and the predicted dominant height of each species. Based on the statistical evaluations, simple linear regression and F-test models developed for the two species showed satisfactory results. Furthermore, the developed models explained about 98.35% and 98.60% of the total variation in the estimate of total dominant height for Acacia mangium and Eucalyptus pellita, respectively. The developed site index curves are expected to be significant for forest managers in predicting the growth patterns and classifying the site productivities of the different stands in Korintiga Hutani plantation.

Notes on the biomass expansion factors of Quercus mongolica and Quercus variabilis forests in Korea

Biomass expansion factors, which convert timber volume (or dry weight) to biomass, are used for estimating the forest biomass and accounting for the carbon budget at a regional or national scale. We estimated the biomass conversion and expansion factors (BCEF), biomass expansion factors (BEF), root to shoot ratio (R), and ecosystem biomass expansion factor (EBEF) for Quercus mongolica Fisch. and Quercus variabilis Bl. forests based on publications in Korea. The mean BCEF, BEF, and R for Q. mongolica was 1.0383 Mg/m 3 (N = 27; standard deviation [SD], 0.5515), 1.3572 (N = 27; SD, 0.1355), and 0.2017 (N = 32; SD, 0.0447), respectively. The mean BCEF, BEF, and R for Q. variabilis was 0.7164 Mg/m 3 (N = 17; SD, 0.3232), 1.2464 (N = 17; SD, 0.0823), and 0.1660 (N = 8; SD, 0.0632), respectively. The mean EBEF, as a simple method for estimating the ground vegetation biomass, was 1.0216 (N = 7; SD, 0.0232) for Q. mongolica forest ecosystems, and 1.0496 (N = 8; SD, 0.0725) for Q. variabilis forest ecosystems. The biomass expansion factor values in this study may be better estimates of forest biomass in Q. mongolica or Q. variabilis forests of Korea compared with the default values given by the Intergovernmental Panel on Climate Change (IPCC).