• Journal of Climate Change Research
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• v.1 no.1
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• pp.31-50
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• 2010

The Arctic climate change for the Last Glacial Maximum(LGM) occurred at 21,000 years ago (21ka) was investigated using simulation results of atmosphere-ocean coupled models from the second phase of the Paleoclimate Modelling Intercomparison Program(PMIP2). In the analysis, we used seven models, the NCAR CCSM of USA, ECHAM3-MPIOM of German Max-Planxk Institute, HadCM3M2 of UK Met Office, IPSL-CM4 of France Laplace Institute, CNRM-CM3 of France Meteorological Institute, MIROC3.2 of Japan CCSR at University of Tokyo, and FGOALS of China Institute of Atmospheric Physics. All the seven models reproduces the Arctic climate features found in the present climate at 0ka(pre-industrial time) in a reasonable degree in comparison to observations. During the LGM, the atmospheric $CO_2$ concentration and other greenhouse gases were reduced, the ice sheets were expanded over North America and northern Europe, the sea level was lowered by about 120m, and orbital parameters were slightly different. These boundary conditions were implemented to simulated LGM climate. With the implemented LGM conditions, the biggest temperature reduction by more than $24^{\circ}C$ is found over North America and northern Europe owing to ice albedo feedback and the change in lapse rate by high elevation. Besides, the expansion of ice sheets leads to the marked temperature reduction by more then $10^{\circ}C$ over the Arctic Ocean. The temperature reduction in northern winter is larger than in summer around the Arctic and the annual mean temperature is reduced by about $14^{\circ}C$. Compared to low mid-latitudes, the temperature reduction is much larger in high northern altitudes in the LGM. This results mirror the larger warming around the Artic in recent century. We could draw some information for the future under global warming from the knowledge of the LGM.

• Korean Journal of Plant Resources
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• v.34 no.4
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• pp.346-361
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• 2021

The range of D. spathulata identified in this survey was between N 35° 24' 58" ~ N 35° 26' 35", E 129° 05' 43" ~ E 129° 07' 04". It is located at an altitude of 98~592 m. The soil pH was strongly acidic in the range of 4.2~4.9, with a canopy openness of 18.56% and a chlorophyll index of 36.74 ± 2.80. As a result of the TWINSPAN analysis, 20 plots of 100 m² each were divided in 4 communities: Pinus densiflora community, Quercus monglica-Diabelia spathulata community, Quercus serrata-Diabelia spathulata community and Carpinus tschonoskii subassociation. The result of species diversity was 0.7615, and evenness and dominance were found to be 0.6077 and 0.3923, respectively. The height of D. spathulata is up to 3.4 m, and the average height is 1.1 m, with most of the species distributed as shrubbery and herbaceous. The average population density of the 20 plots was 1.635 individuals/m², the height range of flowering was 1.0 ~ 1.8 (aver. 1.39 m) and the rate of flowering was 27.37%. It's propagation pattern was mainly formed by extending the rhizome to the side, creating a colony of ground stems.

• Journal of Nutrition and Health
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• v.56 no.1
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• pp.35-53
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• 2023

Purpose: The purpose of the first part of this study was to evaluate the validity of the physical activity classification table for youth (Youth-PACT). The second part of this study was aimed at comparing the estimated energy requirement (EER) with the total energy expenditure (TEE) and evaluating the physical activity patterns of Korean children and adolescents. Methods: The subjects of the first part of the study were 17 children aged 10 to 12 years, and their total energy expenditure (TEE_DLW) was measured using the double labeled water (DLW) method. A total of 166 children and adolescents aged 6-18 years participated in the second part of this study. Their resting energy expenditure (REE) was measured using indirect calorimetry and the TEE_Youth-PACT and physical activity level were calculated by applying the Youth-PACT to the physical activity diary prepared by the subjects. Results: In the first part of this study, there were no significant differences between the TEE_DLW and the TEE_Youth-PACT. The TEE_Youth-PACT accurately predicted TEE_DLW in 37.5% of the subjects. In the second part of the study, the rates at which EER accurately predicted TEE _YouthPACT and overestimated TEE _Youth-PACT were 29.6% and 47.3%, respectively. The time spent based on intensity of physical activity and the physical activity categories which were obtained using Youth-PACT showed different patterns according to sex and age group. Age showed significant positive correlations with REE, TEE, and the time spent in sedentary behavior, but age was significantly negatively correlated with REE/body weight, TEE/body weight, and the time spent in low-intensity and high-intensity activities. Conclusion: The results of this study showed that the Youth-PACT can be used to evaluate the TEE and PAL of children and adolescents. However, further studies are needed to validate the TEE_Youth-PACT and to set the EER for children and adolescents.