• Korean Journal of Environment and Ecology
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• v.37 no.4
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• pp.259-272
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• 2023

This study set up 49 survey areas with an area of about 400 square meters in Abies koreana natural habitat to identify the species composition and vegetation structure of the A. koreana forest in the Mt. Jiri Nation Park, conducted field surveys using phytosociological methods, and performed the cluster analysis using the Two-Way Indicator Species Analysis (TWINSPAN) and Table manipulation. Subsequently, species composition analysis using the importance value, species diversity analysis, DBH analysis, sapling analysis, and similarity analysis was conducted by each cluster type. The cluster analysis classified the A. koreana forest in Mt. Jiri into five clusters, A, B, C, D, and E. The forest was divided into two clusters, Magnolia sieboldii-Dryopteris crassirhizoma-Sasa borealis and Betula ermanii-Solidago virgaurea-Calamagrostis arundinacea. The former was classified as type A and B by Cornus controversa-Hydrangea macrophylla, and the latter was classified as type E, a typical community, and a Sorbus commixta-Rhododendron mucronulatum cluster. And the S. commixta-R. mucronulatum cluster was divided into C type and D type by Picea jezoensis-Ligularia fischeri and Ainsliaea acerifolia. Through vegetation analysis, the importance value of A. koreana, Quercus mongolica, Acer pseudosieboldianum, Fraxinus sieboldiana, and B. ermanii was highly expressed in the A. koreana forest in Mt. Jiri. Regarding species diversity, the results were similar to those reported in other studies of A. koreana forests in Mt. Jiri. The analysis of diameter at breast height (DBH) showed that A. koreana dominated all layers, and the growth of saplings was also good, indicating that the dominance of A. koreana is expected to continue for a while. However, when considering the value of biodiversity that is expected to increase and threats caused by climate change, systematic preservation and management are required to respond to various threats based on continuous monitoring.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.473-481
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• 2022

Environment-friendly harvesting is practiced to maintain ecosystem, landscape, and forest protection functions. The present study was conducted at Simgok-ri, Sinbuk-myeon, Pocheon, Gyeonngi-do, where a 41-50-year-old Japanese larch forest was harvested in an environment-friendly manner from 2017 to 2019. The dynamics of organic matter in this forest were investigated at three years after the harvest. Specifically, organic matter content was measured on the forest floor and in overstory biomass, litterfall, and soil up to 30 cm in depth from June 2020 to January 2021. Owing to the harvest, the amount of overstory biomass of the Japanese larch stands decreased from 142.22 to 44.20 t ha^-1. On the forest floor, the amount of organic matter was 32.87 t ha^-1 in the control plots and 23.34 t ha^-1 in the harvest plots. Annual litterfall was 4.43 t ha^-1 yr^-1 in the control plots and 1.16 t ha^-1 yr^-1 in the harvest plots. Soil bulk density in the B horizon was 0.97 g cm^-3 in the control plots and 1.06 g cm^-3 i n the harvest plots. Soil organic matter content was 11.5% in the control plots and 12.8% in the harvest plots. The total amount of soil organic matter did not differ significantly between the control plots (245.21 t ha^-1) and harvest plots (263.92 t ha^-1), although the amount of soil organic matter tended to be higher in the harvest plots. The total amount of organic matter in the forest was estimated to be 406.48 t ha^-1 in the control plots and 338.21 t ha^-1 in the harvest plots. In the harvest plots, the ratio of aboveground organic matter decreased to 13.1% and soil organic matter increased to 78.0%, indicating that the distribution of organic matter changed significantly in these plots. Overall, the carbon accumulated in aboveground biomass was substantially reduced by environment-friendly harvesting, whereas the soil carbon level increased, which played a role in mitigating the reduction of system carbon in the forest. These results highlight one possible resolution for forest management in terms of coping with climate change. However, given that only three years of environment-friendly harvesting data were analyzed, further research on the dynamics of organic matter and tree growth is needed.

• Journal of Korean Society of Forest Science
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• v.112 no.2
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• pp.173-187
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• 2023

The forest protection policies implemented in South Korea have resulted in the significant accumulation of forest. Moreover, the associated public interest has also been closely evaluated. As forests mature, there arises a need for forest management (FM) practices, such as thinning and harvesting. It is therefore essential to perform a scientific analysis of the long-term effects of FM. In this study, conducted in Mt. Gariwang, the effect of FM on forest succession and wood production (WP) were evaluated based on changes in aboveground biomass (AGB) using the LANDIS-II model. The FM consists of three scenarios (Selection, Shelterwood, and Two-stories), characterized based on the harvest intensity, frequency, and period. The model was applied to changes in the forest over 200 years. All scenarios show that the total AGB decreased immediately after thinning and harvesting. However, AGB recovery time differed among scenarios, with recovery to preharvest level occurring from 15 to 50 years after harvest; further, after 200 years, harvested forests had a greater total AGB than forests without FMs In particular, the changes in AGB of each species was different depending on its shade tolerance. The AGB of currently dominant shade-intolerant and mid-tolerant species decreased dramatically after harvesting. However, shade-tolerant species, dominant in the understory, continued to grow but were not harvested due to their small size. The cumulative WP for each scenario was estimated at 545.6, 141.6, and 299.9 tons/ha in Selection, Shelterwood, and Two-stories, respectively. The composition of WP differed according to harvest intensity and period. Most WP originated from shade-intolerant and mid-tolerant species in the early period. Later, most WP was from shade-tolerant species, which became dominant. The modeling approach used in this study is capable of analyzing the long-term effects of FM on changes in forests and WP. This study can contribute to decision making to guide FM methods for a variety of purposes, including WP and controlling forest composition and structure.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.427-435
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• 2023

Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R². The models with applied correction coefficients achieve R² values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1031-1042
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• 2023

In this study, a deep learning model was developed to predict the yield of cabbage and radish, one of the five major supply and demand management vegetables, using satellite images of Landsat 8. To predict the yield of cabbage and radish in Gangwon-do from 2015 to 2020, satellite images from June to September, the growing period of cabbage and radish, were used. Normalized difference vegetation index, enhanced vegetation index, lead area index, and land surface temperature were employed in this study as input data for the yield model. Crop yields can be effectively predicted using satellite images because satellites collect continuous spatiotemporal data on the global environment. Based on the model developed previous study, a model designed for input data was proposed in this study. Using time series satellite images, convolutional neural network, a deep learning model, was used to predict crop yield. Landsat 8 provides images every 16 days, but it is difficult to acquire images especially in summer due to the influence of weather such as clouds. As a result, yield prediction was conducted by splitting June to July into one part and August to September into two. Yield prediction was performed using a machine learning approach and reference models , and modeling performance was compared. The model's performance and early predictability were assessed using year-by-year cross-validation and early prediction. The findings of this study could be applied as basic studies to predict the yield of field crops in Korea.

• Journal of Korean Society of Forest Science
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• v.113 no.1
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• pp.31-39
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• 2024

This study was performed to determine the effects of Four seedling age classes ageon the characteristics of growth and nutrient uptake in Chamaecyparis obtusa container seedlings. Seedlings (1-1, 2-0, 2-1, and 2-2 seedlings) of C. obtusa grown in containers were harvested to measure specific leaf area, height (H)/root collar diameter (D) ratio, dry mass of aboveground (T)/root dry mass (R) ratio, and seedling quality index of seedlings. The specific leaf area was highest in 1-0 seedlings (30.48 cm² g^-1), whereas it decreased (from 28.62 cm² g^-1 to 23.59 cm² g^-1) with increasing seedling age. The H/D ratio increased with increasing seedling age (from 4.41 in 1-0 seedlings to 8.35 in 2-2 seedlings). The T/R ratio decreased as the seedling age increased (from 4.29 in the 1-0 seedling to 2.13 in the 2-1 seedling). The seedling quality index increased with increasing seedling age (from 0.10 for the 1-0 seedling to 3.06 for the 2-2 seedling). The carbon concentrations of seedling components (leaf, branches, stem, and roots) did not differ significantly with seedling age, whereas the nitrogen concentration of seedling components was the lowest in 2-1 seedlings, as no fertilizer was applied to discourage excessive growth of the seedlings. Phosphorus, potassium, and magnesium concentrations in 2-1 seedling components were not affected by the lack of fertilizer application. These results can be applied to determine the optimum morphological characteristics and nutrient management by seedling age in container- grown C. obtusa.