• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.1-14
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• 2022

To alleviate the urban heat island phenomenon, this study aims to quantitatively analyze the effects of neighborhood green spaces on the improvement of the thermal environment based on detailed scenarios of five types of green spaces, including parks, pocket parks, parking lot greening, roadside planting, and rooftop-wall greening. The ENVI-met 4.4.6v model, a microclimate simulation program, was used to analyze the effects of green spaces. As a result, it was found that the air temperature decreased as the planting density of the park increased, but the thermal comfort index PET, which is the degree of heat sensation felt by humans, was not directly proportional to temperature. The establishment of a pocket park reduced air temperature up to a radius of 56m, while the range of temperature reduction increased by about 12.5% when three additional pocket parks were established at 250m intervals. Unlike the air temperature, PET was only affected in the vicinity of the planted area, so there was no significant difference in the thermal comfort of the surrounding environment due to the construction of pocket parks. Changing the surface pavement from asphalt to lawn blocks and implementing rooftop or wall greening did not directly act as solar shading but positively affected air temperature reduction; PET showed no significant difference. Roadside planting showed a higher air temperature reduction effect as the planting interval was narrower, but PET was not directly proportional to tree density. In the case of shrub planting under trees, it did not significantly affect the air temperature reduction but positively affected the improvement of thermal comfort. This study can outline strategies for constructing neighborhood green spaces to solve the urban heat island phenomena and establish detailed strategies for efficient thermal environment improvements.

• Journal of Mushroom
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• v.21 no.1
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• pp.22-32
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• 2023

To investigate the effect of thinning intensity on environmental factors and ectomycorrhizal mushroom fruiting in forest ecosystems, we studied canopy closure, throughfall, soil temperature, soil moisture, light response of understory vegetation, and ectomycorrhizal mushroom fruiting in a 10-year-old pine forest after 34%, 45%, and 60% thinning. Canopy closure was significantly higher in the 34% treatment and control plots, ranging from 80-85% in April. However, in November, all thinning treatment plots showed a decrease of approximately 5-10% compared with the control plot. The 60% treatment plot had over 200 mm of additional throughfall compared with the control plot, and monthly throughfall was significantly higher by more than 100 mm in October. The soil temperature in each treatment plot increased significantly by up to 1℃ or more compared with the control plot as the thinning rate increased. The soil moisture increased by more than 5% in the thinning treatment plots during rainfall, particularly in the 34% treatment plot, where the rate of moisture decrease was slower. The photosynthetic rate of major tree species (excluding Pinus densiflora)was highest in Quercus mongolica, with a rate of 7 µmolCO₂·m^-2·s^-1. At a lightintensity of 800 μmol·m^-2·s^-1, Q. mongolica showed the highest photosynthetic level of 6 ± 0.3 μmolCO₂·m^-2·s^-1 in the 45% treatment. The photosynthetic rate of Fraxinus sieboldiana and Styrax japonicus increased as the thinning intensity increased. The Shannon-Wiener index of mycorrhizal mushrooms did not significantly differ among treatments, but the fresh weight of mushrooms was approximately 360-840 g higher in the 34% and 45% treatments than in the control. Additionally, the fresh weight of fungi in the 60% treatment was 860 g less than that in the control. There were more individuals of Amanita citrina in the control than in the thinning treatment, while Suillus bovinus numbers increased by more than 10 times in the 34% thinning treatment compared with the control.

• Journal of Korean Society of Forest Science
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• v.112 no.1
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• pp.83-92
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• 2023

This study was established to investigate the site environment of mixed forests in Korea and to estimate the growth and yield of stands using national forest resources inventory data. The growth of mixed forests was derived by applying the Chapman-Richards model with diameter at breast height (DBH), height, and cross-sectional area at breast height (BA), and the yield of mixed forests was derived by applying stepwise regression analysis with factors such as cross-sectional area at breast height, site index (SI), age, and standing tree density per ha. Mixed forests were found to be growing in various locations. By climate zone, more than half of them were distributed in the temperate central region. By altitude, about 62% were distributed at 101-400 m. The fitness indexes (FI) for the growth model of mixed forests, which is the independent variable of stand age, were 0.32 for the DBH estimation, 0.22 for the height estimation, and 0.18 for the basal area at breast height estimation, which were somewhat low. However, considering the graph and residual between the estimated and measured values of the estimation equation, the use of this estimation model is not expected to cause any particular problems. The yield prediction model of mixed forests was derived as follows: Stand volume =-162.6859+6.3434 ∙ BA+9.9214 ∙ SI+0.7271 ∙ Age, which is a step- by-step input of basal area at breast height (BA), site index (SI), and age among several growth factors, and the determination coefficient (R²) of the equation was about 96%. Using our optimal growth and yield prediction model, a makeshift stand yield table was created. This table of mixed forests was also used to derive the rotation of the highest production in volume.

• Journal of Korean Society of Forest Science
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• v.112 no.1
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• pp.40-56
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• 2023

Tree species within the Populus genus grow rapidly and have an excellent capacity to absorb carbon, conferring substantial ability to effective purify the environment. Poplar breeding can be achieved rapidly and efficiently if a genetic linkage map is constructed and quantitative trait loci (QTLs) are identified. Here, a high-density genetic linkage map was constructed for the control pollinated progeny using the genotyping-by-sequencing (GBS) technique, which is a next-generation sequencing method. A search was also performed for the genes associated with quantitative traits located in the genetic linkage map by examining the variables of height and diameter at root collar, and resilience to insect damage. The height and diameter at root collar were measured directly, while the ability to recover from insect damage was scored in a 4-year-old breeding population of aspen hybrids (Odae19 × Bonghyeon4 F1) established in the research forest of Seoul National University. After DNA extraction, paternity was confirmed using five microsatellite markers, and only the individuals for which paternity was confirmed were used for the analysis. The DNA was cut using restriction enzymes and the obtained DNA fragments were prepared using a GBS library and sequenced. The analyzed results were sorted using Populus trichocarpa as a reference genome. Overall, 58,040 aligned single-nucleotide polymorphism (SNP) markers were identified, 17,755 of which were used for mapping genetic linkages. The genetic linkage map was divided into 19 linkage groups, with a total length of 2,129.54 cM. The analysis failed to identify any growth-related QTLs, but a gene assumed to be related to recovery from insect damage was identified on linkage group (chromosome) 4 through genome-wide association study.

• 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.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.325-338
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• 2023

Korean fir (Abies koreana Wilson) is one of the most important environmental indicator tree species for assessing climate change impacts on coniferous forests in the Korean Peninsula. However, due to the nature of alpine and subalpine regions, it is difficult to conduct regular field surveys of Korean fir, which is mainly distributed in regions with altitudes greater than 1,000 m. Therefore, this study analyzed the vegetation change trend of Korean fir using regularly observed remote sensing data. Specifically, normalized difference vegetation index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS), land surface temperature (LST), and precipitation data from Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievalsfor GPM from September 2003 to 2020 for Hallasan and Jirisan were used to analyze vegetation changes and their association with environmental variables. We identified a decrease in NDVI in 2020 compared to 2003 for both sites. Based on the NDVI difference maps, areas for healthy vegetation and high mortality of Korean fir were selected. Long-term NDVI time-series analysis demonstrated that both Hallasan and Jirisan had a decrease in NDVI at the high mortality areas (Hallasan: -0.46, Jirisan: -0.43). Furthermore, when analyzing the long-term fluctuations of Korean fir vegetation through the Hodrick-Prescott filter-applied NDVI, LST, and precipitation, the NDVI difference between the Korean fir healthy vegetation and high mortality sitesincreased with the increasing LST and decreasing precipitation in Hallasan. Thissuggests that the increase in LST and the decrease in precipitation contribute to the decline of Korean fir in Hallasan. In contrast, Jirisan confirmed a long-term trend of declining NDVI in the areas of Korean fir mortality but did not find a significant correlation between the changes in NDVI and environmental variables (LST and precipitation). Further analyses of environmental factors, such as soil moisture, insolation, and wind that have been identified to be related to Korean fir habitats in previous studies should be conducted. This study demonstrated the feasibility of using satellite data for long-term monitoring of Korean fir ecosystems and investigating their changes in conjunction with environmental conditions. Thisstudy provided the potential forsatellite-based monitoring to improve our understanding of the ecology of Korean fir.

• Korean Journal of Environment and Ecology
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• v.37 no.3
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• pp.182-191
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• 2023

This study was carried out to identify the distribution and growth characteristics and evaluate the conservation status of the Michelia compressa Maxim., a rare and endangered wild plant II, in the habitats in Korea. A total of 314 individuals were found in the natural habitats of Heuksan Island and Jeju Island and were divided into four populations. About 45.9% (144 individuals) were distributed in the range of 401m~500m above sea level. The average height of trees was 2.7(±4.8)m, the diameter at breast height was 12.6(±13.9)cm, and the number of branches was 1.0(±0.5) on average. 54.3% of the sapling individuals of M. compressa were distributed within a radius of 30 m from the mother tree, 25.8% were distributed between 31 m through 40 m, and most (90.1%) were distributed within a radius of 60 m. The fact that sapling individuals of M. compressa are not identified even around some mature individuals and appear only in extremely limited areas is estimated to be closely related to the growth conditions as well as the environment of the natural habitats. The dispersal of M. compressa is presumed to be related to the birds and natural seedlings because water puddles, a resting place for birds beyond the range of natural seedlings, characterize its habitats. The IUCN Red List evaluation criteria at the regional and national level of M. compressa corresponds to the Critically Endangered category, and the domestic population under the category of "CR B2ab(v); C2a(i); D."

• Journal of Korea Water Resources Association
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• v.56 no.5
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• pp.311-323
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• 2023

In order to reduce disaster damage by localized heavy rains, floods, and urban inundation, it is important to know in advance whether natural disasters occur. Currently, heavy rain watch and heavy rain warning by the criteria of the Korea Meteorological Administration are being issued in Korea. However, since this one criterion is applied to the whole country, we can not clearly recognize heavy rain damage for a specific region in advance. Therefore, in this paper, we tried to reset the current criteria for a special weather report which considers the regional characteristics and to predict the damage caused by rainfall after 1 hour. The study area was selected as Gyeonggi-province, where has more frequent heavy rain damage than other regions. Then, the rainfall inducing disaster or hazard-triggering rainfall was set by utilizing hourly rainfall and heavy rain damage data, considering the local characteristics. The heavy rain damage prediction model was developed by a decision tree model and a random forest model, which are machine learning technique and by rainfall inducing disaster and rainfall data. In addition, long short-term memory and deep neural network models were used for predicting rainfall after 1 hour. The predicted rainfall by a developed prediction model was applied to the trained classification model and we predicted whether the rain damage after 1 hour will be occurred or not and we called this as 1ST-Model. The 1ST-Model can be used for preventing and preparing heavy rain disaster and it is judged to be of great contribution in reducing damage caused by heavy rain.

• 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 Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.258-266
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• 2023

This study analyzed methodologies for estimating carbon stocks of perennial woody crops and the research cases in overseas countries. As a result, we found that Australia, Bulgaria, Canada, and Japan are using the stock-difference method, while Austria, Denmark, and Germany are estimating the change in the carbon stock based on the gain-loss method. In some overseas countries, the researches were conducted on estimating the carbon stock change using image data as tier 3 phase beyond the research developing country-specific factors as tier 2 phase. In South Korea, convergence studies as the third stage were conducted in forestry field, but advanced research in the agricultural field is at the beginning stage. Based on these results, we suggest directions for the following four future researches: 1) securing national-specific factors related to emissions and removals in the agricultural field through the development of allometric equation and carbon conversion factors for perennial woody crops to improve the completeness of emission and removals statistics, 2) implementing policy studies on the cultivation area calculation refinement with fruit tree-biomass-based maturity, 3) developing a more advanced estimation technique for perennial woody crops in the agricultural sector using allometric equation and remote sensing techniques based on the agricultural and forestry satellite scheduled to be launched in 2025, and to establish a matrix and monitoring system for perennial woody crop cultivation areas in the agricultural sector, Lastly, 4) estimating soil carbon stocks change, which is currently estimated by treating all agricultural areas as one, by sub-land classification to implement a dynamic carbon cycle model. This study suggests a detailed guideline and advanced methods of carbon stock change calculation for perennial woody crops, which supports 2050 Carbon Neutral Strategy of Ministry of Agriculture, Food, and Rural Affairs and activate related research in agricultural sector.