• Korean Journal of Environmental Biology
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• v.40 no.4
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• pp.464-476
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• 2022

In recent years, macroalgal bloom occurs frequently in coastal oceans worldwide. It might be attributed to accelerating climate change. "Green tide" events caused by proliferation of green macroalgae (Ulva spp.) not only damage the local economy, but also harm coastal environments. These nuisance events have become common across several coastal regions of continents. In Korea, green tide incidences are readily seen throughout the year along the coastlines of Jeju Island, particularly the northeastern coast, since the 2000s. Ulva species are notorious to be difficult for morphology-based species identification due to their high degrees of phenotypic plasticity. In this study, to investigate temporal variation in Ulva community structure on Jeju Island between 2015 and 2020, chloroplast barcode tufA gene was sequenced and phylogenetically analyzed for 152 specimens from 24 sites. We found that Ulva ohnoi and Ulva pertusa known to be originated from subtropical regions were the most predominant all year round, suggesting that these two species contributed the most to local green tides in this region. While U. pertusa was relatively stable in frequency during 2015 to 2020, U. ohnoi increased 16% in frequency in 2020 (36.84%), which might be associated with rising sea surface temperature from which U. ohnoi could benefit. Two species (Ulva flexuosa, Ulva procera) of origins of Europe should be continuously monitored. The findings of this study provide valuable information and molecular genetic data of genus Ulva occurring in southern coasts of Korea, which will help mitigate negative influences of green tide events on Korea coast.

• Korean Journal of Environmental Biology
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• v.40 no.3
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• pp.267-274
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• 2022

Excess nitrogen (N) flowing from livestock manure to water systems poses a serious threat to the natural environment. Thus, livestock wastewater management has recently drawn attention to this related field. This study first attempted to obtain the optimal conditions for the further volatilization of NH₃ gas generated from pig wastewater by adjusting the amount of injected magnesia (MgO). At 0.8 wt.% of MgO (by pig wastewater weight), the volatility rate of NH₃ increased to 75.5% after a day of aeration compared to untreated samples (pig wastewater itself). This phenomenon was attributed to increases in the pH of pig wastewater as MgO dissolved in it, increasing the volatilization efficiency of NH₃. The initial pH of pig wastewater was 8.4, and the pH was 9.2 when MgO was added up to 0.8 wt.%. Second, the residual ammonia nitrogen (NH₄⁺-N) in pig wastewater was removed by precipitation in the form of struvite (NH₄MgPO₄·6H₂O) by adjusting the pH after adding MgO and H₃PO₄. Struvite produced in the pig wastewater was identified by field emission scanning electron microscopy (FE-SEM) and X-ray diffraction (XRD) analysis. White precipitates began to form at pH 6, and the higher the pH, the lower the concentration of NH₄⁺-N in pig wastewater. Of the total 86.1% of NH₄⁺-N removed, 62.4% was achieved at pH 6, which was the highest removal rate. Furthermore, how struvite changes with pH was investigated. Under conditions of pH 11 or higher, the synthesized struvite was completely decomposed. The yield of struvite in the precipitate was determined to be between 68% and 84% through a variety of analyses.

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.1
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• pp.22-27
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• 2023

This experiment was conducted to confirm the possibility of preparing Sorghum×sudangrass hybrid artificial hay using far-infrared rays in Korea. The machine used in this experiment is a drying device based on far-infrared rays, and is designed to control temperature, air flow rate, far-infrared radiation amount, and air flow speed. The Sorghum×sudangrass hybrids harvested in late September were wilted in the field for one day, and a drying test was performed on them. Conditions for drying were performed by selecting a total of 7 conditions, and each condition induced a change in radiation amount in a single condition (42%) and two steps (4 treatments) and three steps (2 treatments). The speed of the air flow in the device was fixed at 60 m/s, and the run time was changed to 30, 60, and 90 minutes. The average dry matter (DM) content was 82.84%. The DM content was 59.94 and 76.91%, respectively, in drying conditions 1 and 3, which were not suitable for hay. In terms of drying rate, it was significantly higher than 80% in the 5, 6 and 7 treatment, and power consumption was slightly high with an average of 5.7 kw/h. As for the feed value according to each drying condition, the crude protein (CP) content increased as the drying time increased, and there was no significant difference between treatments in ADF, NDF, IVDMD and TDN content. In terms of RFV, treatment 1, which is a single condition, was significantly lower than the complex condition. Through the above results, it was determined that the drying conditions 4 and 5 were the most advantageous when considering the drying speed, power consumption, and quality.

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.1
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• pp.11-21
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• 2023

This study was conducted to estimate the damage of Whole Crop Corn (WCC; Zea Mays L.) according to abnormal climate using machine learning as the Representative Concentration Pathway (RCP) 4.5 and present the damage through mapping. The collected WCC data was 3,232. The climate data was collected from the Korea Meteorological Administration's meteorological data open portal. The machine learning model used DeepCrossing. The damage was calculated using climate data from the automated synoptic observing system (ASOS, 95 sites) by machine learning. The calculation of damage was the difference between the dry matter yield (DMY)_normal and DMY_abnormal. The normal climate was set as the 40-year of climate data according to the year of WCC data (1978-2017). The level of abnormal climate by temperature and precipitation was set as RCP 4.5 standard. The DMY_normal ranged from 13,845-19,347 kg/ha. The damage of WCC which was differed depending on the region and level of abnormal climate where abnormal temperature and precipitation occurred. The damage of abnormal temperature in 2050 and 2100 ranged from -263 to 360 and -1,023 to 92 kg/ha, respectively. The damage of abnormal precipitation in 2050 and 2100 was ranged from -17 to 2 and -12 to 2 kg/ha, respectively. The maximum damage was 360 kg/ha that the abnormal temperature in 2050. As the average monthly temperature increases, the DMY of WCC tends to increase. The damage calculated through the RCP 4.5 standard was presented as a mapping using QGIS. Although this study applied the scenario in which greenhouse gas reduction was carried out, additional research needs to be conducted applying an RCP scenario in which greenhouse gas reduction is not performed.

• Journal of The Korean Society of Grassland and Forage Science
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• v.42 no.1
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• pp.26-31
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• 2022

This study was carried out to evaluate the growth characteristics and forage yield potential for warm season grass as emergency forages. The experimental design was a randomized block design (RBD) with three replications. Two barnyard millet (Echinochloa species cv. Shirohie and Jeju native), a pearl millet (Pennisetum glaucum cv Feed milk 2) a proso millet (Panicum miliaceum cv Native), a teffgrass (Eragrostis tef cv. Tiffany) and a kleingrass (Panicum coloratum cv. Selection 75) were compared for forage production and quality at the Mid regions of Korea. Warm season forage crops were sown on May 21 and June 23 respectively, and in 2021, it was sown twice on May 21 and June 21 The number of days to seedling emergence for barnyard millet and teffgrass was observed approximately 10 and 3 days after seeding, respectively. The cultivation period from seeding to harvest was within 60 days for all entry spices except for the late-heading type barnyard millet (within 84 days). As for the dry matter yield by seeding date, the dry matter yield of the late-heading type barnyard millet in May seeding was the highest at 23,872 kg/ha, and the kleingrass was the lowest at 3,888 kg/ha. For the June seeding, the dry matter yield of the late-heading type barnyard millet was 17,032 kg/ha, the highest, and the proso millet, teffgrass and kleingrass showed the lowest at 5,468, 5,442, and 5,197 kg/ha, respectively. The crude protein (CP) content was varied by warm season grass species, but the early-heading type barnyard millet, teffgrass, and kleingrass showed the highest tendency, and the late-heading type barnyard millet showed the lowest at 5.7~5.9%. Neutral detergent fiber (NDF) and acid detergent fiber (ADF) content did not show a significant difference between the seeding in May, but kleingrass in June sowed lower than the others.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.331-350
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• 2022

This study aims to understand topics of incivility related to COVID-19 from analyzing Twitter posts including COVID-19-related hate speech. To achieve the goal, a total of 63,802 tweets that were created between December 1st, 2019, and August 31st, 2021, covering three targets of hate speech including region and public facilities, groups of people, and religion were analyzed. Frequency analysis, dynamic topic modeling, and keyword co-occurrence network analysis were used to explore topics and keywords. 1) Results of frequency analysis revealed that hate against regions and public facilities showed a relatively increasing trend while hate against specific groups of people and religion showed a relatively decreasing trend. 2) Results of dynamic topic modeling analysis showed keywords of each of the three targets of hate speech. Keywords of the region and public facilities included "Daegu, Gyeongbuk local hate", "interregional hate", and "public facility hate"; groups of people included "China hate", "virus spreaders", and "outdoor activity sanctions"; and religion included "Shincheonji", "Christianity", "religious infection", "refusal of quarantine", and "places visited by confirmed cases". 3) Similarly, results of keyword co-occurrence network analysis revealed keywords of three targets: region and public facilities (Corona, Daegu, confirmed cases, Shincheonji, Gyeongbuk, region); specific groups of people (Coronavirus, Wuhan pneumonia, Wuhan, China, Chinese, People, Entry, Banned); and religion (Corona, Church, Daegu, confirmed cases, infection). This study attempted to grasp the public's anti-citizenship public opinion related to COVID-19 by identifying domestic COVID-19 hate targets and keywords using social media. In particular, it is meaningful to grasp public opinion on incivility topics and hate emotions expressed on social media using data mining techniques for hate-related to COVID-19, which has not been attempted in previous studies. In addition, the results of this study suggest practical implications in that they can be based on basic data for contributing to the establishment of systems and policies for cultural communication measures in preparation for the post-COVID-19 era.

• Journal of Life Science
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• v.32 no.3
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• pp.189-195
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• 2022

Kinesin-2 comprises two subfamilies of the heterotrimeric or homodimeric motors found in mammalian cells. Heterotrimeric kinesin-2 consists of kinesin superfamily proteins (KIFs) 3A and 3B and kinesin-associated protein 3 (KAP3), which is a molecular motor protein that moves along microtubules. It plays diverse roles in cargo transport, including anterograde trafficking in cilia, and interacts with many different cargoes and proteins, but their binding proteins have not yet been fully identified. In this study, the yeast two-hybrid assay was used to identify the proteins that interact with the cargo-binding domain (CBD) of KIF3A, and an interaction between KIF3A and brain expressed X-linked 2 (Bex2) was found. Bex2 bound to the CBD-containing C-terminal tail region of KIF3A but did not interact with the same region of KIF3B or KIF5A (a motor protein of kinesin-1). KIF3A interacted with another isoform, Bex1, but did not interact with Bex3. In addition, glutathione S-transferase (GST) pull-downs showed that KIF3A specifically interacts with GST-Bex1 and GST-Bex2 but not with GST alone. When co-expressed in HEK-293T cells, Bex2 co-localized with KIF3A and co-immunoprecipitated with KIF3A and KIF3B but not KIF5B. In combination, these results suggest that Bex2 is capable of binding to heterotrimeric kinesin-2 and may serve as an adaptor protein that links heterotrimeric kinesin-2 with cargo.

• Journal of Korean Society of Forest Science
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• v.111 no.1
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• pp.115-124
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• 2022

This study was conducted to obtain basic data that could help prevent damage caused by slow-moving landslides (land-creep). Specifically, the geological, topographic, and physical characteristics of land-creep were analyzed in Jiphyeon-myeon, Jinju-si. The first and second analyzed land-creeps occurred in 1982 and 2019, respectively. The area damaged in the second land-creep was about 11.5-fold larger than that damaged in the first land-creep. The dominant constituent rock in the land-creep area was sedimentary rock, which seems to be weakly resistant to weathering. The areas that collapsed due to land-creep were related to the presence of separated rocks between the bedding plane in the estimated activity surface over the slope direction and the vertically developed joint surface. Thus, surface water and soil debris were introduced through the gaps of separated rocks. Additionally, the areas collapsed due to the combination of the bedding plane and joint surface shale and sandstone showed an onion structure of weathered outcrop from the edge to inner part caused by weathering from ground water. Consequently, core stones were formed. The study area was a typical area of land-creep in a mountain caused by ground water. Land-creep was classified into convex areas of colluvial land-creep. The landslide-risk rating in the study area was classified into three and five classes. The flow of ground water moved to the northeast and coincided with the direction of the collapse. Soil bulk density in the collapsed area was lower than that in ridge area, which was rarely affected by land-creep. Thus, soil bulk density was affected by the soil disturbance in the collapsed area.

• Korean Journal of Ecology and Environment
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• v.55 no.1
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• pp.60-75
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• 2022

The Bayesian algorithm model is a model algorithm that calculates probabilities based on input data and is mainly used for complex disasters, water quality management, the ecological structure between living things or living-non-living factors. In this study, we analyzed the main factors affected Korean Estuary Trophic Diatom Index (KETDI) change based on the Bayesian network analysis using the diatom community and physicochemical factors in the domestic estuarine aquatic ecosystem. For Bayesian analysis, estuarine diatom habitat data and estuarine aquatic diatom health (2008~2019) data were used. Data were classified into habitat, physical, chemical, and biological factors. Each data was input to the Bayesian network model (GeNIE model) and performed estuary aquatic network analysis along with the nationwide and each coast. From 2008 to 2019, a total of 625 taxa of diatoms were identified, consisting of 2 orders, 5 suborders, 18 families, 141 genera, 595 species, 29 varieties, and 1 species. Nitzschia inconspicua had the highest cumulative cell density, followed by Nitzschia palea, Pseudostaurosira elliptica and Achnanthidium minutissimum. As a result of analyzing the ecological network of diatom health assessment in the estuary ecosystem using the Bayesian network model, the biological factor was the most sensitive factor influencing the health assessment score was. In contrast, the habitat and physicochemical factors had relatively low sensitivity. The most sensitive taxa of diatoms to the assessment of estuarine aquatic health were Nitzschia inconspicua, N. fonticola, Achnanthes convergens, and Pseudostaurosira elliptica. In addition, the ratio of industrial area and cattle shed near the habitat was sensitively linked to the health assessment. The major taxa sensitive to diatom health evaluation differed according to coast. Bayesian network analysis was useful to identify major variables including diatom taxa affecting aquatic health even in complex ecological structures such as estuary ecosystems. In addition, it is possible to identify the restoration target accurately when restoring the consequently damaged estuary aquatic ecosystem.

• Korean Journal of Ecology and Environment
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• v.55 no.1
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• pp.1-9
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• 2022

An estuary is an area where a freshwater river or stream meets the ocean. Even before the importance of the value of estuaries was recognized, the estuary was lost because of large-scale conversion by draining, filling, damming, and dredging. In South Korea, 643 estuaries are located, and the total area is 3,248,300 ha, accounting for 32.5% of the total area of South Korea. Over 35% of Korean estuaries are closed estuaries which are only temporally connected with the sea, either permanently or periodically. Since 2008, in order to preserve the estuary ecosystem and solve major issues in the estuary by accumulating knowledge about the estuarine ecosystem, the Ministry of Environment of Republic of Korea has been conducting the "Estuarine Ecosystem Monitoring and Assessment Project". At 668 sites of 325 estuaries, epilithic diatom, benthic macroinvertebrate, fish, and vegetation are investigated, and the habitat condition of each site is evaluated using the newly developed biotic index. More than 100 researchers annually record 2,097 species of estuaries according to the standardized survey guidelines over the past 14 years and provide strictly managed data necessary for establishing estuaries conservation policies. As a result of bibliometric analysis of 1,195 research articles related to the monitoring and assessment of the estuarine ecosystem, research on pollutants such as heavy metals and sediment control have recently been conducted. "Estuarine Ecosystem Monitoring and Assessment Project" is an ecological monitoring type of long-term mandated monitoring that is usually focused on identifying trends. Although it is difficult to identify the mechanism influencing a change in an ecosystem through long-term mandated monitoring, providing empirical data for supporting evidence-based policy, decision-making, and the management of ecosystems. In order to increase the efficiency of the project, research to investigate the relationship between sediments and pollutants and organisms can be conducted at specific estuaries or sites to compensate for the shortcomings of mandatory monitoring.