• Korean Journal of Environment and Ecology
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• v.30 no.2
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• pp.199-213
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• 2016

This study aimed to analyze the vegetation characteristics of the coastal forests and to figure out if there is possibilities to develop the forests into mixed stand multistory forests and to suggest some sound management practices. The vegetat- ion structure and flora of four sites; Kijipo, Chunjangdae, Janghang and Kusipo in the west coastal forests in Korea were investigated and analyzed in the present study. In the every site, Pinus thunbergii was dominating the tree layer in the forests. And P. densiflora, Robinia pseudoacacia, Quercus serrata, Prunus sargentii var. sargentii, Q. acutissima and Castanea crenata were dominating the subtree layers in some sites. P. thunbergii stands in four sites would maintain for a while since the populat- ion density of middle aged group is higher than those of young and old groups. According to the geographical location conditions, there is a possibility that the coastal forests in Kusipo site would progress into oak tree stands in the long run. The biodiversity was quite high to have 205 taxa in the study sites. To induce the coastal forests into multistory forests, P. thunbergii stands need to be thinned. And then creating the environment including making some pathways and site usage rest-riction is needed to let new diverse plants could come in and grow for a success-ful multistory forests.

• Korean Journal of Environment and Ecology
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• v.36 no.6
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• pp.651-661
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• 2022

Plants social network analysis, which combines plants society and social network analyses, is a new research method for understanding plants society. This study was conducted to investigate the relationship between species, using plant social network analysis targeting Taejongdae in Busan, and build basic data for management. Taejongdae, located in the warm temperate forest in Korea, is a representative coastal forest of Busan Metropolitan City, and the Pinus thunbergii-Eurya japonicacommunity is widely distributed. This study set up 100 quadrats (size of 100m²each) in Taejongdae to investigate the species that emerged and analyzed the interspecies association focusing on major species. Based on the results, a sociogram was created using the Gephi 0.9.2, and the network centrality and structure were analyzed. The results showed that the frequency of appearance was high in the order of P. thunbergii, E. japonica, Quercus serrata, Sorbus alnifolia, Ligustrum japonicum, and Styrax japonicusand that many evergreen broad-leaved trees appeared due to the environmental characteristics of the site. The plants social network of Taejongdae was composed of a small-scale network with 50 nodes and 172 links and was divided into 4 groups through modularization. The succession sere identified through a sociogram confirmed that the group that include P. thunbergiiand E. japonicawould progress to a deciduous broadleaf community dominated by Q. serrataand Carpinus tschonoskii, using hub nodes such as Prunus serrulataf. spontaneaand Toxicodendron trichocarpum. Another succession sere was highly likely to progress to an evergreen broad-leaved community dominated by Machilus thunbergiiand Neolitsea sericea, using M. thunbergiias a medium. In some areas, a transition to a deciduous broad-leaved community dominated by Celtis sinensis, Q. variabilisand Zelkova serratausing Lindera obtusilobaand C. sinensisas hub nodes was expected.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.715-727
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• 2023

To provide detailed and appropriate meteorological information in mountainous areas, the Korea Forest Service has established an Automatic Mountain Meteorology Observation Station (AMOS) network in major mountainous regions since 2012, and 464 stations are currently operated. In this study, we proposed an optimal kriging technique with lapse rate correction to produce gridded temperature data suitable for Korean forests using AMOS point observations. First, the outliers of the AMOS temperature data were removed through statistical processing. Then, an optimized theoretical variogram, which best approximates the empirical variogram, was derived to perform the optimal kriging with lapse rate correction. A 500-meter resolution Kriging map for temperature was created to reflect the elevation variations in Korean mountainous terrain. A blind evaluation of the method using a spatially unbiased validation sample showed a correlation coefficient of 0.899 to 0.953 and an error of 0.933 to 1.230℃, indicating a slight accuracy improvement compared to regular kriging without lapse rate correction. However, the critical advantage of the proposed method is that it can appropriately represent the complex terrain of Korean forests, such as local variations in mountainous areas and coastal forests in Gangwon province and topographical differences in Jirisan and Naejangsan and their surrounding forests.

• Korean Journal of Environmental Biology
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• v.35 no.3
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• pp.380-388
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• 2017

Factors affecting spatial distribution of halophytes were analyzed in June 2012 at the Goraebul coastal dunes. In the Goraebul sand dune, distribution of halophytes was divided into three groups. The first group belonging to Elymus mollis, Carex kobomugi, Calystegia soldanella, Ixeris repens and Glehnia littoralis was distributed in the ridge of primary sand dune and dune slack. The second group belonging to Lathyrus japonicus and Zoysia macrostachya was distributed in the dune slack. The third group belonging to Pinus thunbergii, Vitex rotundifolia and Linaria japonicus was distributed in the pine forest of the secondary sand dune. E. mollis, C. kobomugi, C. soldanella, I. repens and G. littoralis was distributed in relatively unstable habitat of sand dunes due to the large amount of sand movement. V. rotundifolia was distributed in a relatively stable habitat. Factors that have the greatest influence on distribution of halophytes in the Goraebul sand dunes are distance from the seashore, topography, and the pine forest. The Goraebul sand dune is a relatively well-preserved area with minimal human intervention. Therefore, different distribution of physico-chemical factors by natural processes is essential to spatial distribution of halophytes than other sand dunes in Korea. Significant natural processes in the Goraebul sand dunes were advance and retreat of coastlines from waves, erosion and sedimentation of sand due to wind and waves, and dispersal of seawater.

• Journal of Environmental Impact Assessment
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• v.26 no.6
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• pp.385-403
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• 2017

This study showed the national ecosystem classification for the spatial standards of ecosystems-based approaches to the risk assessments and adaptation plan. The characteristics of climate change risk assessment, implement national adaptation plans, and ecosystem/habitat classification status was evaluated. Focusing on the land cover classification widely utilized as spatial data for the assessments of biodiversity and ecosystem services in the UK and other countries in Europe, the applicability of the national land cover classification for climate change risk assessments was reviewed. Considering the ecosystem classification for climate change risk assessment and establishing adaptation measures, it is difficult to apply rough classification method to the land cover system because of lack of information on habitat trend by categorization. The results indicated that forest ecosystems and agro-ecosystem occupied 62.3% and 25.0% of land cover, respectively, of the entire country. Although the area is small compared with the land area, wetland ecosystem (2.9%), marine ecosystem (0.4%), coastal ecosystem (0.6%), and urban ecosystem (6.1%) can be included in the risk assessments. Therefore, it is necessary to subdivide below the medium classification for the forest and agricultural land, as well as Inland wetland, which has a higher proportion of habitat preference of taxa than land area, marine/coastal habitat, and transition areas such as urban and natural ecosystem.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.229-237
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• 2019

This study was conducted to estimate annual reference evapotranspiration (ET₀) for the agro-climatic zones for rice paddy fields in South Korea between 1980 and 2015. The daily ET₀ was estimated by applying the Penman-Monteith method to meteorological data from 61 weather stations provided by Korean Meteorological Administration (KMA). The average of annual ET₀ from 1980 to 2015 was 1334.1±33.89 mm. The ET₀ was the highest at the Southern Coastal Zone due to their higher air temperature and lower relative humidity. The ET₀ had significantly increased with 2.81 mm/yr for the whole zones over 36 years. However, the change rate of it was different among agro-climatic zones. The annual ET₀ highly increased in central zones and eastern coastal zones. In terms of correlation coefficient, the temporal change of the annual ET₀ was closely related to variations of four meteorological factors (i.e., mean, minimum temperatures, sunshine duration, and relative humidity). The results demonstrated that whole Korean agro-climatic zones have been undergoing a significant change in the annual ET₀ for the last 36 years. Understanding the spatial pattern and the long-term variation of the annual ET₀ associated with global warming would be useful to improve crop and water resource managements at each agro-climatic zone of South Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.179-188
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• 2012

A kiwifruit cultivar 'Hayward' has been grown in Jeju Island where the current climate is suitable for growth and development of this crop. Prediction of the geographical shift in the phenology can help the kiwifruits growers to adapt to the local climate change in the future. Two phenology models (i.e., chill-day and DVS) were parameterized to estimate flowering date of kiwifruits 'Hayward' based on the data collected from field plots and chamber experiments in the southern coastal and island locations in South Korea. Spatio-temporally independent datasets were used to evaluate performance of the two models in predicting flowering date of 'Hayward'. Chill-day model showed better performance than DVS model (2.5 vs. 4.0 days in RMSE). Daily temperature data interpolated at a higher spatial resolution over Jeju Island were used to predict flowering dates of 'Hayward' in 2021-2100 under the A1B scenario. According to the model calculation under the future climate condition, the flowering of kiwifruits shall accelerate and the area with poor flowering might increase due to the warmer winter induced insufficient chilling. Optimal land area for growing 'Hayward' could increase for a while in the near future (2021-2030), whereas such areas could decrease to one half of the current areas by 2100. The geographic locations suitable for 'Hayward' cultivation would migrate from the current coastal area to the elevated mountain area by 250 m.

• Korean Journal of Environment and Ecology
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• v.29 no.1
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• pp.14-20
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• 2015

We created species richness maps of mammals, birds and plants using "Nnational Ecosystem Survey" data and identified correlations between species richness maps of each taxa. We examine the distribution of species richness of each taxa and calculated conservation priority rank through plotting species-area curves using an additive benefit function in Zonation. The conclusions of this study are as follows. First, plant showed high species richness in Gangwon province and Baekdudaegan, and mammals showed high species richness at eastern slope of Baekdudaegan in Gangwon province unusually and the species richness of mammals distributed equally except Gyeonggi and Chungnam province. However, birds showed high species richness in the west costal because the area is the major route of winter migratory birds. Second, correlation of each taxa's distribution is not significant. Correlation between mammals and birds is positive but correlations between birds and others are negative. Because mammals inhabit in forest but birds mostly live in coastal wetlands and rivers. Therefore, bird's habitats are not shared with other habitats. Third, the probability of mammals occurrence is very low under 25% in species-area curve, others increase proportionally to area. Birds increase dramatically richness at 10% because bird's habitat is concentrated in coastal wetlands and rivers. Plants increased gently species richness due to large forest in Gangwon province. We can calculate the predicted number of species in curves and plan various conservation strategies using the marginal number of species. Finally, high priority ranks for conservation distributed mainly in Gangwon province and Baekdudaegan. When we compared with priority map and terrestrial national parks, the parks were evaluated as high priority ranks. However, the rank of parks away from Baekdudaegan was low. This study has the meaning of selecting conservation priority area using National Ecosystem Survey. In spite of the omission of survey data in national parks and Baekdudaegan, the results were good. Therefore, the priority rank method using species distribution models is useful to selecting protected areas and improving conservation plans. However, it is needed to select protected areas considering various evaluation factors, such as rarity, connectivity, representativeness, focal species and so on because there is a limit to select protected area only using species richness.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.21 no.3
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• pp.103-111
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• 2016

Seasonal dynamics of kelp forest-forming algae, Ecklonia cava population formed following the large-scale disturbance by Typhoon 'Bolaven' in August 2012 were investigated in Jeju Island, Korea. Morphological characteristics, recruits density, mortality rate, total density and biomass were monitored bimonthly from June 2013 to June 2015. Total and longest blade lengths, and individual weight of E. cava showed distinct seasonal trends. Stipe length increased from winter to spring, but did not show increase or reduced from summer to autumn. This indicates that morphological characteristics of E. cava are mainly affected by the change of blades. The optimal temperature for E. cava growth was about $15-18^{\circ}C$ during winter to spring while the growths were inhibited at the water temperature above $20^{\circ}C$ during summer. E. cava exhibited very low recruitment during spring-summer. However, high recruitment was observed on April 2015 when canopy cover was very low due to low density. This indicates that recruitment of E. cava was controlled not by seasonal effects but by physical factors such as canopy and space. The mortality rate of juvenile plants was highest due to their unstable settlement. By June 2015, 34 months after the disturbances, E. cava was almost recovered to the pre-disturbance population size structure. These results suggest that recovery of kelp forest following the large-scale disturbance requires a considerable period of time (more than three years). This study should provide valuable ecological information on management, restoration and protection of kelp species.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.4
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• pp.109-118
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• 2022

The data of the missing section among the vertex surface sea temperature observation data was imputed using the Bidirectional Recurrent Neural Network(BiRNN). Among artificial intelligence techniques, Recurrent Neural Networks (RNNs), which are commonly used for time series data, only estimate in the direction of time flow or in the reverse direction to the missing estimation position, so the estimation performance is poor in the long-term missing section. On the other hand, in this study, estimation performance can be improved even for long-term missing data by estimating in both directions before and after the missing section. Also, by using all available data around the observation point (sea surface temperature, temperature, wind field, atmospheric pressure, humidity), the imputation performance was further improved by estimating the imputation data from these correlations together. For performance verification, a statistical model, Multivariate Imputation by Chained Equations (MICE), a machine learning-based Random Forest model, and an RNN model using Long Short-Term Memory (LSTM) were compared. For imputation of long-term missing for 7 days, the average accuracy of the BiRNN/statistical models is 70.8%/61.2%, respectively, and the average error is 0.28 degrees/0.44 degrees, respectively, so the BiRNN model performs better than other models. By applying a temporal decay factor representing the missing pattern, it is judged that the BiRNN technique has better imputation performance than the existing method as the missing section becomes longer.