• Mycobiology
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• v.49 no.6
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• pp.551-558
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• 2021

The Federated States of Micronesia (FSM) is an island country in the western Pacific and is a known biodiversity hotspot. However, a relatively small number of fungi (236 species) have been reported till July 2021. Since fungi play major ecological roles in ecosystems, we investigated the fungal diversity of FSM from various sources over 2016 and 2017 and constructed a local fungal inventory, which also included the previously reported species. Fruiting bodies were collected from various host trees and fungal strains were isolated from marine and terrestrial environments. A total of 99 species, of which 78 were newly reported in the FSM, were identified at the species level using a combination of molecular and morphological approaches. Many fungal species were specific to the environment, host, or source. Upon construction of the fungal inventory, 314 species were confirmed to reside in the FSM. This inventory will serve as an important basis for monitoring fungal diversity and identifying novel biological resources in FSM.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.245-256
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• 2021

This study was conducted to identify the applicability of a LiDAR sensor to forest resources inventories by comparing data on a tree's position, height, and DBH obtained by the sensor with those by existing forest inventory methods, for the tree species of Criptomeria japonica in Jeolmul forest in Jeju, South Korea. To this end, a backpack personal LiDAR (Greenvalley International, Model D50) was employed. To facilitate the process of the data collection, patterns of collecting the data by the sensor were divided into seven ones, considering the density of sample plots and the work efficiency. Then, the accuracy of estimating the variables of each tree was assessed. The amount of time spent on acquiring and processing the data by each method was compared to evaluate the efficiency. The findings showed that the rate of detecting standing trees by the LiDAR was 100%. Also, the high statistical accuracy was observed in both Pattern 5 (DBH: RMSE 1.07 cm, Bias -0.79 cm, Height: RMSE 0.95 m, Bias -3.2 m), and Pattern 7 (DBH: RMSE 1.18 cm, Bias -0.82 cm, Height: RMSE 1.13 m, Bias -2.62 m), compared to the results drawn in the typical inventory manner. Concerning the time issue, 115 to 135 minutes per 1ha were taken to process the data by utilizing the LiDAR, while 375 to 1,115 spent in the existing way, proving the higher efficiency of the device. It can thus be concluded that using a backpack personal LiDAR helps increase efficiency in conducting a forest resources inventory in an planted coniferous forest with understory vegetation, implying a need for further research in a variety of forests.

• Atmosphere
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• v.33 no.1
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• pp.61-72
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• 2023

Accurate estimation of forest carbon stocks is important in establishing greenhouse gas reduction plans. In this study, we estimate the spatial distribution of forest carbon stocks using machine learning techniques based on high-resolution remote sensing data and detailed field survey data. The high-resolution remote sensing data used in this study are Landsat indices (EVI, NDVI, NDII) for monitoring vegetation vitality and Shuttle Radar Topography Mission (SRTM) data for describing topography. We also used the forest growing stock data from the National Forest Inventory (NFI) for estimating forest biomass. Based on these data, we built a model based on machine learning methods and optimized for Korean forest types to calculate the forest carbon stocks per grid unit. With the newly developed estimation model, we created forest carbon stocks maps and estimated the forest carbon stocks in South Korea. As a result, forest carbon stock in South Korea was estimated to be 432,214,520 tC in 2020. Furthermore, we estimated the loss of forest carbon stocks due to the Donghae-Uljin forest fire in 2022 using the forest carbon stock map in this study. The surrounding forest destroyed around the fire area was estimated to be about 24,835 ha and the loss of forest carbon stocks was estimated to be 1,396,457 tC. Our model serves as a tool to estimate spatially distributed local forest carbon stocks and facilitates accounting of real-time changes in the carbon balance as well as managing the LULUCF part of greenhouse gas inventories.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.3
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• pp.17-28
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• 2022

We evaluated the effect of CO₂ offsetting by estimating changes in carbon uptake under various forest management scenarios and proposed forest management strategies to achieve carbon neutrality. Paju and Goseong, which have relatively large forest areas but different industrial characteristics, were selected for the study sites. The current state of forest distribution was analyzed using forest type maps and aerial photographs, and the amount of carbon uptake was calculated using the equation presented by the IPCC Guidelines for National Greenhouse Gas Inventories and the national emission/absorption coefficients from the Korea National Greenhouse Gas Inventory Report. As of 2015, the forest carbon absorption in Paju and Goseong was 49,931 t/yr and 94,225 t/yr, respectively, and the annual carbon absorption per unit area was 2.28 t/ha/yr and 2.16 t/ha/yr. Under the forest management scenarios, the annual maximum carbon absorption per unit area is estimated to increase to 5.68 t/ha/yr in Paju and 4.22 t/ha/yr in Goseong, and this absorption would increase further if urban forests were additionally created. Even if the current forests of Paju and Goseong are maintained as they are, emissions from electricity use can be sufficiently offset. However, by applying appropriate forest management strategies, emissions from sectors other than electricity use could be offset. This study can be applied to the establishment of carbon absorption strategies in the forest sector to achieve carbon neutrality.

• Journal of Climate Change Research
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• v.8 no.4
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• pp.415-424
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• 2017

This study was conducted to estimate carbon stocks of Pinus densiflora with drawing volume of trees in each tree height and DBH applying the suitable stem taper equation and tree specific carbon emission factors, using collected growth data from all over the country. Information on distribution area, tree age, tree number per hectare, tree volume and volume stocks were obtained from the $5^{th}$ National Forest Inventory (2006~2010) and Statistical yearbook of forest (2016), and method provided in IPCC GPG was applied to estimate carbon stock and uptake. Performance in predicting stem diameter at a specific point along a stem in Pinus densiflora by applying Kozak's model, $d=a_{1}DBH^{a_2}a_3^{DBH}X^{b_{1}Z^2+b_2ln(Z+0.001)+b_3\sqrt{Z}+b_4e^z+b_5(\frac{DBH}{H})}$, which is well known equation in stem taper estimation, was evaluated with validations statistics, Fitness Index, Bias and Standard Error of Bias. Consequently, Kozak's model turned out to be suitable in all validations statistics. Stem volume table of P. densiflora was derived by applying Kozak's model and carbon stock tables in each tree height and DBH were developed with country-specific carbon emission factors ($WD=0.445t/m^3$, BEF = 1.445, R = 0.255) of P. densiflora. As the results of analysis in carbon uptake for each province, the values were high with Gangwon-do $9.4tCO_2/ha/yr$, Gyeongsandnam-do and Gyeonggi-do $8.7tCO_2/ha/yr$, Chungcheongnam-do $7.9tCO_2/ha/yr$ and Gyeongsangbuk-do $7.8tCO_2/ha/yr$ in order, and Jeju-do was the lowest with $6.8tC/ha/yr$. Total carbon stocks of P. densiflora were 127,677 thousands tC which is 25.5% compared with total percentage of forest and carbon stock per hectare (ha) was $84.5tC/ha/yr$ and $7.8tCO_2/ha/yr$, respectively.

• 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 Climate Change Research
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• v.5 no.2
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• pp.127-137
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• 2014

The main purpose of this study is to estimate tradial growth response and to predict the potential spatial distribution of major tree species(Pinus densiflora, Quercus mongolica, Quercus spp., Castanea crenata and Larix kaempferi) in South Korea, considering climate and topographic factors. To estimate radial growth response, $5^{th}$ National Forest Inventory data, Topographic Wetness Index (TWI) and climatic data such as temperature and precipitation were used. Also, to predict the potential spatial distribution of major tree species, RCP 8.5 Scenario was applied. By our analysis, it was found that the rising temperature would have negative impacts on radial growth of Pinus densiflora, Castanea crenata and Larix kaempferi, and positive impacts on that of Quercus mongolica, Quercus spp.. Incremental precipitation would have positive effects on radial growth of Pinus densiflora and Quercus mongolica. When radial growth response considered by RCP 8.5 scenario, it was found that the radial growth of Pinus densiflora, Castanea crenata and Larix kaempferi would be more vulnerable than that of Quercus mongolica and Quercus spp. to temperature. According to the climate change scenario, Quercus spp. including Quercus mongolica would be expected to have greater abundance than its present status in South Korea. The result of this study would be helpful for understanding the impact of climatic factors on tree growth and for predicting the distribution of major tree species by climate change in South Korea.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.502-510
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• 2022

In the national greenhouse gas inventory, a settlements category has never been included owing to the lack of activity data. Therefore, this study was conducted to obtain basic data for estimating biomass carbon storage in settlements. Nondestructive stem analysis with a laser dendrometer was performed on four major street tree species (Metasequoia glyptostroboides, Prunus armeniaca, Ginkgo biloba, and Acer buergerianum) in Wonju city, South Korea. Allometric equations of the aboveground volume were developed using five models, and allometric equations of crown area were developed with diameter at breast height (DBH) as an independent variable. The best performing allometric equations were aD²+bD+c for M.glyptostroboides and G. biloba, aD+bD² for P. armeniaca, and a+bD² for A. buergerianum. Regarding the allometric equations of crown area with DBH as an independent variable, G. biloba and A. buergerianum exhibited low coefficients of determination (R²), i.e., < 0.364, whereas M. glyptostroboides and P. armeniaca exhibited satisfactory R² values, i.e., > 0.767, probably due to different street tree management practices. The allometricequations in this study will support the carbon inventory of settlements and urban tree monitoring in management practices.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1155-1164
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• 2023

Currently, the National Forest Inventory (NFI) collects tree information by human, so the range and time of the survey are limited. Research is actively being conducted to extract tree information from a large area using aerial Light Detection And Ranging (LiDAR) and aerial photographs, but it does not reflect the characteristics of forest areas in Korea because it is conducted in areas with wide tree spacing or evenly spaced trees. Therefore, this study proposed a methodology for generating Digital Surface Model (DSM), Digital Elevation Model (DEM), and Canopy Height Model (CHM) images using aerial LiDAR, extracting the tree height through the local Maxima, and calculating the Diameter at Breath Height (DBH) through the DBH-tree height formula. The detection accuracy of trees extracted through the proposed methodology was 88.46%, 86.14%, and 84.31%, respectively, and the Root Mean Squared Error (RMSE) of DBH calculated based on the tree height formula was around 5cm, confirming the possibility of using the proposed methodology. It is believed that if standardized research on various types of forests is conducted in the future, the scope of automation application of the manual national forest resource survey can be expanded.

• Journal of Korean Society of Forest Science
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• v.85 no.4
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• pp.586-595
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• 1996

The purpose of this study was to examine the effects of participation in a forest program on the level of depression changes in the participants. Total of 501 university students residing in the middle province of Korea were administered Beck Depression Inventory(BDI). Among them, 32 students were selected as participants of the program based on the scores of the BDI. A 5-day forest program included climbing, sharing experience with others and so on. Pre and post tests control group research design was employed for this study, with BDI measures taken from each of 32 participants on three time frames : 2 weeks before the program, immediately before participation, and immediately after participation. BDI scores were expected to decrease as a result of forest program participation. The study results supported this hypothesis.