• Journal of Ecology and Environment
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• v.38 no.1
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• pp.15-23
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• 2015

This study was conducted in an effort to provide important clues pertaining to the conservation and restoration of Aporia crataegi by identifying the spatial distribution characteristics of the current habitats, prospective habitats, and future habitats of A. crataegi in accordance with climate changes. To determine the distribution of A. crataegi, data from a total of 36 collecting points throughout South Korea, North Korea, China, Japan, Mongolia, and Russia are used. The spatial distributions of the data were examined through MaxEnt modeling. The distribution probability rates exceeded 75% at 18 locations among the 36 species occurrence locations, with Gangwon province showing the highest distribution probability in South Korea. The precision of the MaxEnt model was remarkably high, with an AUC value of 0.982. The variables that affect the potential distribution of A. crataegi by more than 10% are the degree of temperature seasonality, the amount of precipitation in the warmest quarter, the annual mean temperature, and the amount of precipitation in the driest month, in that order of importance. It was found that the future potential distribution area of A. crataegi continuously moves northward over time up to 2070s. In addition, the area of the potential distribution showing a habitable probability rate that exceeds 75% in northeast Asia was $28,492km^2$, where the area of potential distribution in the north part of Korean peninsula was $20.404km^2$ in size. Thus, it is anticipated that the most important future habitats of A. crataegi in the northeast Asia will be North and South Hamgyeong provinces and Ryanggang province near Mt. Baekdoosan in the northern area of the Korean peninsula.

• The Korean Journal of Applied Statistics
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• v.26 no.3
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• pp.413-420
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• 2013

Stochastic weather generator is a commonly used tool to simulate daily weather time series. Recently, a generalized linear model(GLM) has been proposed as a convenient approach to tting these weather generators. In the present paper, a stochastic weather generator is considered to model the time series of daily temperatures for Seoul South Korea. As a covariate, precipitation occurrence is introduced to a relate short-term predictor to short-term predictands. One of the limitations of stochastic weather generators is a marked tendency to underestimate the observed interannual variance of monthly, seasonal, or annual total precipitation. To reduce this phenomenon, we incorporate a time series of seasonal mean temperatures in the GLM weather generator as a covariate.

• Journal of Climate Change Research
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• v.6 no.3
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• pp.243-248
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• 2015

This study was conducted to predict the changes of potential distribution for invasive alien plant, Conyza bonariensis in Korea. C. bonariensis was found in southern Korea (Jeju, south coast, southwest coast). The habitats of C. bonariensis were roadside, bare ground, farm area, and pasture, where the interference by human was severe. Due to the seed characteristics of Compositae, C. bonariensis take long scattering distance and it will easily spread by movement of wind, vehicles and people. C. canadensis in same Conyza genus has already spread on a national scale and it is difficult to manage. We used maximum entropy modeling (MaxEnt) for analyzing the environmental influences on C. bonariensis distribution and projecting on two different RCP scenarios, RCP 4.5 and RCP 8.5. The results of our study indicated annual mean temperature, elevation and temperature seasonality had higher contribution for C. bonariensis potential distribution. Area under curve (AUC) values of the model was 0.9. Under future climate scenario, the constructed model predicted that potential distribution of C. bonariensis will be increased by 338% on RCP 4.5 and 769% on RCP 8.5 in 2100s.

• Journal of Ecology and Environment
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• v.45 no.4
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• pp.313-327
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• 2021

Background: Citizen science is becoming a mainstream approach of baseline data collection to monitor biodiversity and climate change. Dragonflies (Odonata) have been ranked as the highest priority group in biodiversity monitoring for global warming. Ischnura senegalensis Rambur has been designated a biological indicator of climate change and is being monitored by the citizen science project "Korean Biodiversity Observation Network." This study has been performed to understand changes in the distribution range of I. senegalensis in response to climate change using citizen science data in South Korea. Results: We constructed a dataset of 397 distribution records for I. senegalensis, ranging from 1980 to 2020. The number of records sharply increased over time and space, and in particular, citizen science monitoring data accounted for the greatest proportion (58.7%) and covered the widest geographical range. This species was only distributed in the southern provinces until 2010 but was recorded in the higher latitudes such as Gangwon-do, Incheon, Seoul, and Gyeonggi-do (max. Paju-si, 37.70° latitude) by 2020. A species distribution model showed that the annual mean temperature (Bio1; 63.2%) and the maximum temperature of the warmest month (Bio5; 16.7%) were the most critical factors influencing its distribution. Future climate change scenarios have predicted an increase in suitable habitats for this species. Conclusions: This study is the first to show the northward expansion in the distribution range of I. senegalensis in response to climate warming in South Korea over the past 40 years. In particular, citizen science was crucial in supplying critical baseline data to detect the distribution change toward higher latitudes. Our results provide new insights on the value of citizen science as a tool for detecting the impact of climate change on ecosystems in South Korea.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.696-700
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• 2004

In the Korean seas, Sea Surface Temperature (SST) and Thermal Fronts (TF) were analyzed temporally and spatially during 8 years from 1993 to 2000 using NOAA/AVHRR MCSST. As the result of harmonic analysis, distributions of the mean SST were $10~25^{\circ}C,$ and generally SST decreased as latitude increased. SST increased in the order as following; the South Sea $(20\~23^{\circ}C),$ the East Sea $(17\~19^{\circ}C)$, and the West $Sea(13\~16^{\circ}C).$ Annual amplitudes and phases were $4\~11^{\circ}C,\;210\~240^{\circ}$ and high values were shown as following; the West Sea $(A1,\;9\~11^{\circ}C),$ the Northern East Sea $(A5,\;8\~9^{\circ}C),$ the Southern East Sea $(A4,\;6\~8^{\circ}C),$ the South Sea $(A3,\;6\~7^{\circ}C),$ the East China Sea $(A2,\;4\~7^{\circ}C)$ and phases; $A3\;(238\~242^{\circ}),\;A4\;(235\~240^{\circ}),\;A5\;(225\~235^{\circ}),\;Al\;(220\~230^{\circ}),\;A2\;(210\~235^{\circ}),$ respectively, Both of them were related inversely except the area A2, therefore the rest areas were affected by seasonal variations. TF were detected by Soble Edge Detection Method using gradient of SST. Consequently, TF were divided into 4 fronts; the Subpolar Front (SPF) based on the Cold Water Mass (low SST and salinity Subartic Water), resulting from the North Korea Cold Current (NKCC) and the East Sea Proper Cold Water in the middle and low layer, and the Warm Water Mass (high SST and salinity Subtropical Water), resulting from the Tsushima Warm Current (TWC) in area A4 and 5, the Kuroshio Front (KF) based on the Kuroshio Current (KC) and shelf waters in the East China Sea (ESC) in A2, and the South Sea Coastal Front (SSCF) based on the South Sea Coastal Water (SSCW) and TWC in A3. Also, the Tidal Front was weakly appeared in AI. TF located in steep slope of submarine topography. Annual amplitudes and phases were bounded in the same place, and these results should be considered to influence of seasonal variations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2B
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• pp.141-153
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• 2009

The occurrence causes of the extreme rainfall to happen in Korea can be distinguished with the typhoons and local downpours. The typhoon events attacked irregularly to induce the heavy rainfall, and the local downpour events mean a seasonal rain front and a local rainfall. Almost every year, the typhoons and local downpours that induced a heavy precipitation be generated extreme disasters like a flooding. Consequently, in this research, There were distinguished the causes of heavy rainfall events with the typhoons and the local downpours at Korea. Also, probability precipitation was computed according to the causes of the local downpour events. An evaluation of local downpours can be used for analysis of heavy rainfall event in short period like a flash flood. The methods of calculation of probability precipitation used the parametric frequency analysis and the Empirical Simulation Technique (EST). The correlation analysis was computed between annual maximum precipitation by local downpour events and sea surface temperature, moisture index for composition of input vectors. At the results of correlation analysis, there were revealed that the relations closely between annual maximum precipitation and sea surface temperature. Also, probability precipitation using EST are bigger than probability precipitation of frequency analysis on west-middle areas in Korea. Therefore, region of west-middle in Korea should prepare the extreme precipitation by local downpour events.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.2
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• pp.96-104
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• 2001

Usage of ecosystem models has been extended to landscape scales for understanding the effects of environmental factors on natural and agro-ecosystems and for serving as their management decision tools. Accurate prediction of spatial variation in daily temperature is required for most ecosystem models to be applied to landscape scales. There are relatively few empirical evaluations of landscape-scale temperature prediction techniques in mountainous terrain such as Korean Peninsula. We derived a periodic function of seasonal lapse rate fluctuation from analysis of elevation effects on daily temperatures. Observed daily maximum and minimum temperature data at 63 standard stations in 1999 were regressed to the latitude, longitude, distance from the nearest coastline and altitude of the stations, and the optimum models with $r^2$ of 0.65 and above were selected. Partial regression coefficients for the altitude variable were plotted against day of year, and a numerical formula was determined for simulating the seasonal trend of daily lapse rate, i.e., partial regression coefficients. The formula in conjunction with an inverse distance weighted interpolation scheme was applied to predict daily temperatures at 267 sites, where observation data are available, on randomly selected dates for winter, spring and summer in 2000. The estimation errors were smaller and more consistent than the inverse distance weighting plus mean annual lapse rate scheme. We conclude that this method is simple and accurate enough to be used as an operational temperature interpolation scheme at landscape scale in Korea and should be applicable to elsewhere.

• Korean Journal of Environmental Agriculture
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• v.36 no.3
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• pp.169-174
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• 2017

BACKGROUND:Kiwifruit growers build their vineyards using many windbreaks to protect their kiwifruit vines from defoliation injury by strong winds such as typhoon. In this study, we have compared fruit quality, budbreak rate and floral bud as affected by windbreaks. And also we surveyed several microclimate indices of kiwifruit orchard depending on the covering materials of arch-type windbreaks. METHODS AND RESULTS: Five different windbreak materials including polyethylene film (PE), blue- and white-colored nets were tested in pipe-framed archtype kiwifruit vineyards as the covering materials. Photosynthetically active radiation (PAR), annual mean temperature (AMT) and chill unit (CU) as well as fruit quality were compared among the covering materials. In all treatments, annual PAR was more than $400{\mu}mol\;m^{-2}s^{-1}$, in which kiwifruit leaf could reach its maximum photosynthesis, since the leaves were emerged. Annual mean temperature was greater in 0.1 mm-PE covering as much as $1-2^{\circ}C$ than other windbreaks. In CU calculated by three different models, all windbreaks showed more than 1400 CU that is fully fulfilled CU for kiwifruit rest completion. There were no difference in budbreak rate among the covering materials. Fruit weight was heavier in 0.1 mm-PE and white-net (4 mm) than other windbreaks. CONCLUSION: Regardless of the windbreak materials, the PAR quantity was enough for kiwifruit photosynthesis. And CU for kiwifruit rest completion was fully achieved in all treatments. However, with respect to fruit weight, quantity of PAR, and AMT, etc., It is highly recommended for kiwifruit growers to choose 0.1 mm-PE and white-net (4 mm) as for their windbreaks materials.

• Korean Journal of Environmental Biology
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• v.35 no.4
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• pp.492-500
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• 2017

The purpose of this study was to investigate the seasonal distribution of phytoplankton as prey for oysters and to characterize the environmental factors controlling their abundance from June 2016 to May 2017, in the northeast coast between Tongyeong and Saryang Island, particularly for the oyster farming area. During the survey period, water temperature changed from $7.54^{\circ}C$ in February to $29.5^{\circ}C$ in August. The abnormal high temperature persisted during one month in August. Salinity was low due to summer rainfall and typhoon. The lowest level was 30.68 psu in September, and it peaked at 34.24 psu in May. The dissolved oxygen (DO) concentration ranged from $6.0-9.45mg\;L^{-1}$, and the DO concentration in the surface layer was like that in the bottom layers. The seasonal trends of pH were also like those of DO. The pH ranged from 7.91 to 8.50. Nitrate with nitrite, phosphate, and silicate concentrations ranged from $0.14{\mu}M$ to $7.66{\mu}M$, from $0.01{\mu}M$ to $4.16{\mu}M$, and from $0.27{\mu}M$ to $20.33{\mu}M$, respectively. The concentration of chlorophyll a (Chl. a) ranged from $0.37{\mu}g\;L^{-1}$ to $2.44{\mu}g\;L^{-1}$ in the surface layer. The annual average concentration was $1.26{\mu}g\;L^{-1}$. The annual mean phytoplankton community comprised Bacillariophyta (69%), Dinophyta (17%), and Cryptophyta (10%), respectively. Dinoflagellate Prorocentrum donghaiense in June was the most dominant at 90%. In the summer, diatom Chaetoceros decipiens, Rhizosolenia setigera and Pseudo-nitzschia delicatissima were dominant. These species shifted to diatom Chaetoceros spp. and Crytophyta species in autumn. In the winter, high densities of Skeletonema spp. and Eucampia zodiacus were maintained. Therefore, the researchers thought that the annual mean Chl. a concentration was relatively lower to sustain oyster feeding, implying that the prey organism (i.e., phytoplankton) was greatly controlled by continuous filter feeding behavior of oyster in the vicinity area of the oyster culture farm.

• Journal of the Korean earth science society
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• v.21 no.2
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• pp.137-158
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• 2000

The correlation and Empirical Orthogonal Function (EOF) analyses over the globe have been applied to intercompare lower-stratospheric (${\sim}$70hPa) temperature obtained from satellite data and two model reanalyses. The data is the19 years (1980-98) Microwave Sounding Unit (MSU) channel 4 (Ch4) brightness temperature, and the reanalyses are GCM (NCEP, 1980-97; GEOS, 1981-94) outputs. In MSU monthly climatological anomaly, the temperature substantially decreases by ${\sim}$21k in winter over southern polar regions, and its annual cycle over tropics is weak. In October the temperature and total ozone over the area south of Australia remarkably increase together. High correlations (r${\ge}$0.95) between MSU and reanalyses occur in most global areas, but they are lower (r${\sim}$O.75) over the 20-3ON latitudes, northern America and southern Andes mountains. The first mode of MSU and reanalyses for monthly-mean Ch4 temperature shows annual cycle, and the lower-stratospheric warming due to volcanic eruptions. The analyses near the Korean peninsula show that lower-stratospheric temperature, out of phase with that for troposphere, increases in winter and decreases in summer. In the first mode for anomaly over the tropical Pacific, MSU and reanalyses indicate lower-stratospheric warming due to volcanic eruptions. In the second mode MSU and GEOS present Quasi-Biennial Oscillation (QBO) while NCEP, El Ni${\tilde{n}}$o. Volcanic eruption and QBO have more impact on lower-stratospheric thermal state than El Ni${\tilde{n}}$o. The EOF over the tropical Atlantic is similar to that over the Pacific, except a negligible effect of El Ni${\tilde{n}}$o. This study suggests that intercomparison of satellite data with model reanalyses may estimate relative accuracy of both data.