• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.

• Journal of Korean Society of Disaster and Security
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• v.16 no.4
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• pp.45-59
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• 2023

The global focus on mitigating climate change has traditionally centered on carbon dioxide, but recent attention has shifted towards methane as a crucial factor in climate change adaptation. Natural settings, particularly aquatic environments such as wetlands, reservoirs, and lakes, play a significant role as sources of greenhouse gases. The accumulation of organic contaminants on the lake and reservoir beds can lead to the microbial decomposition of sedimentary material, generating greenhouse gases, notably methane, under anaerobic conditions. The escalation of methane emissions in freshwater is attributed to the growing impact of non-point sources, alterations in water bodies for diverse purposes, and the introduction of structures such as river crossings that disrupt natural flow patterns. Furthermore, the effects of climate change, including rising water temperatures and ensuing hydrological and water quality challenges, contribute to an acceleration in methane emissions into the atmosphere. Methane emissions occur through various pathways, with ebullition fluxes-where methane bubbles are formed and released from bed sediments-recognized as a major mechanism. This study employs Biochemical Methane Potential (BMP) tests to analyze and quantify the factors influencing methane gas emissions. Methane production rates are measured under diverse conditions, including temperature, substrate type (glucose), shear velocity, and sediment properties. Additionally, numerical simulations are conducted to analyze the relationship between fluid shear stress on the sand bed and methane ebullition rates. The findings reveal that biochemical factors significantly influence methane production, whereas shear velocity primarily affects methane ebullition. Sediment properties are identified as influential factors impacting both methane production and ebullition. Overall, this study establishes empirical relationships between bubble dynamics, the Weber number, and methane emissions, presenting a formula to estimate methane ebullition flux. Future research, incorporating specific conditions such as water depth, effective shear stress beneath the sediment's tensile strength, and organic matter, is expected to contribute to the development of biogeochemical and hydro-environmental impact assessment methods suitable for in-situ applications.

• Journal of the Korea Organic Resources Recycling Association
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• v.17 no.3
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• pp.27-39
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• 2009

The main objective of this study is to investigate the characteristics of combustion by analyzing fuel gases from a combustion equipment with various combustion conditions for refuse-derived fuels (RDFs). CO gas is a parameter for indicating of incomplete combustion during a combustion process. The lowest CO gas was produced when the experiment conditions were m=2 under air-fuel condition and $800^{\circ}C$. $CO_2$ gas is a final product after complete combustions. The highest amount of $CO_2$ gas was produced when the experiment conditions were m=2 under air-fuel condition and $800^{\circ}C$. The highest level of $SO_2$ gas was produced in S.1 sample containing the highest sulfur. The highest level of NOx gas was produced in S.1 sample with the highest nitrogen content and air-fuel condition of m=2 under temperature of $800^{\circ}C$. HCl gas that is generated by reacting with metals catalyst through oxygen catalyst reaction during combustion process is a precursor of dioxin formation. The higher level of HCl gas was produced in the sample with higher chlorine content. The lowest level of HCl gas was produced when the experiment conditions were air-fuel condition of m=2 and $800^{\circ}C$. The lowest level of $NH_3$ gas was generated when the experiment condition was m=2 under air-fuel condition and after 3 minutes. Air-fuel condition is more important to create $NH_3$ gas than operating temperatures. Higher level of $H_2S$ gas was generated in S.1 sample with the higher sulfur content and was created in RDFs that contain higher mixture ratios of sewage sludge and food wastes. A result of combustion, gases and gases levels from the combustion of S.1 and S.2 were very similar to the combustion of a stone coal. As results of this research, when evaluating the feasibility of the RDFs, the RDFs could be used as auxiliary and main fuels.

• Applied Biological Chemistry
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• v.29 no.1
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• pp.62-72
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• 1986

At present, the definition and chemical analysis method of available soil phosphorus for plants have not been standardized because of the complexity of crop and soil characteristics in Korea and many analysis methods have been suggested with different extraction conditions. Suitable analytical method of available soil P should be established by the trial of various methods based on crop nutrition and soil conditions. To establish the most suitable analysis method of available soiIP, a pot experiment with young maize was conducted over 44 different upland soils collected over the land of Korea. The amount of uptaken P by the plant was determined by ten different chemical methods for the available soil P. The results obtained were as follows: 1. Total phosphorus content in the sample soils ranged ranged $533{\sim}4917\;ppm$, and showed significant positive correlation with the content of organic matter. 2. The P content was relatively low in the acid sulfate soil and very high in the volcanic ash soil although both types of soil contained high level of orgic matter. 3. The amount of extractable P determined by ten different methods were varied more or less, and the ratios of the extractable P to the total soil P were in the range of $1{\sim}48%$. 4. The relative values to the amount of extractable soil P by different methods were in the order of $H_2O(5\;min.)\;1.0\;<\;H_2O(60min.)\;2.27\;<\;NH_4HCO_3\;5.57\;<\;NaHCO_3\;7.42\;<\;Double\;lactate\;9.71\;<\;Bray\;No.1\;12.53\;<\;Lancaster\;17.63\;<\;Nelson\;25.96\;<\;AcOH\;27.6\;<\;CAL-method\;50.27$ 5. The amount of extractable P determined by all of applied methods was very low in acid sulfate soil, volcanic ash soil and coarse textured soil. 6. Soil pH and total soil P generally showed significant positive correlation with the chemically extracted P, and soil organic matter was negatively correlated with the determined by Nelson-and CAL-method. Olsen method which showed significant correlation with exchangeable calcium seemed to be recommendable for calcareous soils. 7. Total amount of uptaken P by Young maize through continuos twice cropping was 4.05% of total soil P in average, and the uptake in the second cropping was twice as much as that of the first cropping. 8. Three determination methods, i.e. Soltanpour-, Double lactate and Bray No. 1-method seemed to be more suitable than Lancaster method which is widely practiced at present in Korea. However, further study should be carried out with other crops and soils to most adequate chemical method for determination of available soil P.

• Korean Journal of Soil Science and Fertilizer
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• v.5 no.2
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• pp.1-38
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• 1972

This study, designed to establish a classification system of paddy soils and suitability groups on productivity and management of paddy land based on soil characteristics, has been made for the paddy soils on the Gimje-Mangyeong plains. The morphological, physical and chemical properties of the 15 paddy soil series found on these plains are briefly as follows: Ten soil series (Baeggu, Bongnam, Buyong, Gimje, Gongdeog, Honam, Jeonbug, Jisan, Mangyeong and Suam) have a B horizon (cambic B), two soil series (Geugrag and Hwadong) have a Bt horizon (argillic B), and three soil series (Gwanghwal, Hwagye and Sindab) have no B or Bt horizons. Uniquely, both the Bongnam and Gongdeog series contain a muck layer in the lower part of subsoil. Four soil series (Baeggu, Gongdeog, Gwanghwal and Sindab) generally are bluish gray and dark gray, and eight soil series (Bongnam, Buyong, Gimje, Honam, Jeonbug, Jisan, Mangyeong and Suam) are either gray or grayish brown. Three soil series (Geugrag, Hwadong and Hwagye), however, are partially gleyed in the surface and subsurface, but have a yellowish brown to brown subsoil or substrata. Seven soil series (Bongnam, Buyong, Geugrag, Gimje, Gongdeog, Honam and Hwadong) are of fine clayey texture, three soil series (Baeggu, Jeonbug and Jisan) belong to fine loamy and fine silty, three soil series (Gwanghwal, Mangyeong and Suam) to coarse loamy and coarse silty, and two soil series (Hwagye and Sindab) to sandy and sandy skeletal texture classes. The carbon content of the surface soil ranges from 0.29 to 2.18 percent, mostly 1.0 to 2.0 percent. The total nitrogen content of the surface soil ranges from 0.03 to 0.25 percent, showing a tendency to decrease irregularly with depth. The C/N ratio in the surface soil ranges from 4.6 to 15.5, dominantly from 8 to 10. The C/N ratio in the subsoil and substrata, however, has a wide range from 3.0 to 20.25. The soil reaction ranges from 4.5 to 8.0. All soil series except the Gwanghwal and Mangyeong series belong to the acid reaction class. The cation exchange cpacity in the surface soil ranges from 5 to 13 milliequivalents per 100 grams of soil, and in all the subsoil and substrata except those of a sandy texture, from 10 to 20 milliequivalents per 100 grams of soil. The base saturation of the soil series except Baeggu and Gongdeog is more than 60 percent. The active iron content of the surface soil ranges from 0.45 to 1.81 ppm, easily-reduceable manganese from 15 to 148 ppm, and available silica from 36 to 366 ppm. The iron and manganese are generally accumulated in a similar position (10 to 70cm. depth), and silica occurs in the same horizon with that of iron and manganese, or in the deeper horizons in the soil profile. The properties of each soil series extending from the sea shore towards the continental plains change with distance and they are related with distance (x) as follows: y(surface soil, clay content) = $$-0.2491x^2+6.0388x-1.1251$$ y(subsoil or subsurface soil, clay content) = $$-0.31646x^2+7.84818x-2.50008$$ y(surface soil, organic carbon content) = $$-0.0089x^2+0.2192x+0.1366$$ y(subsoil or subsurface soil, pH) = $$-0.0178x^2-0.04534x+8.3531$$ Soil profile development, soil color, depositional and organic layers, soil texture and soil reaction etc. are thought to be the major items that should be considered in a paddy soil classification. It was found that most of the soils belonging to the moderately well, somewhat poorly and poorly drained fine and medium textured soils and moderately deep fine textured soils over coarse materials, produce higher paddy yields in excess of 3,750 kg/ha. and most of the soils belonging to the coarse textured soils, well drained fine textured soils, moderately deep medium textured soils over coarse materials and saline soils, produce yields less than 3,750kg/ha. Soil texture of the profile, available soil depth, salinity and gleying of the surface and subsurface soils etc. seem to be the major factors determining rice yields, and these factors are considered when establishing suitability groups for paddy land. The great group, group, subgroup, family and series are proposed for the classification categories of paddy soils. The soil series is the basic category of the classification. The argillic horizon (Bt horizon) and cambic horizon (B horizon) are proposed as two diagnostic horizons of great group level for the determination of the morphological properties of soils in the classification. The specific soil characteristics considered in the group and subgroup levels are soil color of the profile (bluish gray, gray or yellowish brown), salinity (salic), depositonal (fluvic) and muck layers (mucky), and gleying of surface and subsurface soils (gleyic). The family levels are classified on the basis of soil reaction, soil texture and gravel content of the profile. The definitions are given on each classification category, diagnostic horizons and specific soil characteristics respectively. The soils on these plains are classified in eight subgroups and examined under the existing classification system. Further, the suitability group, can be divided into two major categories, suitability class and subclass. The soils within a suitability class are similar in potential productivity and limitation on use and management. Class 1 through 4 are distinguished from each other by combination of soil characteristics. Subclasses are divided from classes that have the same kind of dominant limitations such as slope(e), wettness(w), sandy(s), gravels(g), salinity(t) and non-gleying of the surface and subsurface soils(n). The above suitability classes and subclasses are examined, and the definitions are given. Seven subclasses are found on these plains for paddy soils. The classification and suitability group of 15 paddy soil series on the Gimje-Mangyeong plains may now be tabulated as follows.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.6
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• pp.439-446
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• 2009

Nitrogen balance in the regional scale which was calculated the difference between nitrogen input and output was estimated to assess the impact of rice cultivation on water environment. Nitrogen balances in Gyeonggi province, where nitrogen concentration in irrigation water was high and in Chungnam province, where nitrogen absorbtion by rice was high, were -5.4 and -8.3 kg $-8.3kg\;ha^{-1}\;yr^{-1}$, respectively. Nitrogen balances of paddy field in Gangwon province, where nitrogen output was small and irrigation water was clean, and in Gyeongnam province, where organic matter content of soil was high and rice yield was low, were 4.9 and $14.0kg\;ha^{-1}\;yr^{-1}$, respectively. Average nitrogen balance and total nitrogen absorption of paddy field in Korea were estimated to $-0.3kg\;ha^{-1}\;yr^{-1}$ and $-3,315Mg\;yr^{-1}$, respectively. When the nitrogen concentration in irrigation water was increased by $1mg \;L^{-1}$, nitrogen balance of rice paddy changed by $-2.91kg\;ha^{-1}\;yr^{-1}$. Also, when nitrogen fertilizer applied was decreased from 110 to $90kg\;ha^{-1}$ and the same harvest was maintained, the nitrogen absorption by rice paddy from irrigation water was estimated to increase by 10,600 Mg per year in Korea. However, in cases, the harvest was reduced to either 90% or 85%, nitrogen balances were changed from -11.7 to -2.3 and $2.4kg\;ha^{-1}$, respectively. These results suggest that the reduction of nitrogen fertilizer use may not always lead to a negative nitrogen balance and sustainable agriculture can achieve by not cutting down the use of fertilizer only but by reduction of fertilizer application concurrently by maintenance of harvest and by utilization of environmental characteristics such as nutrient contents in irrigation water and soils.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1565-1576
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• 2023

An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (R_rs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This R_rs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of R_rs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ R_rs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for R_rs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying R_rs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.

• Korean Journal of Soil Science and Fertilizer
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• v.40 no.5
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• pp.418-428
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• 2007

Physical and chemical properties of the aggregate by-products including sludge and crushed dust samples collected from the 21 private companies throughout the country were analyzed to evaluate possible usage of the by-products as artificial soil materials for plantation. The pH of the materials ranged from 8.0 to 11.0. The organic matter content was $2.85g\;kg^{-1}$, and the total nitrogen content and available phosphate content were low as 0.7 percents and $12.98mg\;kg^{-1}$, respectively. Exchangeable $Ca^{2+}$, $Mg^{2+}$, $K^+$, and $Na^+$ were 2.29, 0.47, 0.02 and $0.05cmol\;kg^{-1}$, respectively. Heavy metal contents were lower than the limits regulated by environmental law of Korea. Textural analysis showed that most of the materials were silt loam with low water holding capacity ranged from 0.67 to 7.41 percents, and with low hydraulic conductivity ranged from 0.4 to $2.8m\;s^{-1}$. Mineralogical analysis showed that the aggregate by product materials were mostly composed of silicate, alumina and ferric oxides except calcium oxide dominant materials derived from limestones. The primary minerals were quartz, feldspars and dolomites derived from granite and granitic gneiss materials. Some samples derived from limestone material showed calcite and graphite together with the above minerals. According to the result, it can be concluded that the materials could be used as the artificial soil material for plantation after proper improvement of the physico-chemical properties and fertility.

• Journal of Korean Society of Forest Science
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• v.52 no.1
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• pp.58-71
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• 1981

Thecodiplosis japonesis is sweeping the Pinus densiflora forests from south-west to north-east direction, destroying almost all the aged large trees as well as even the young ones. The front line of infestation is moving slowly but ceaselessly norhwards as a long bottle front. Estimation is that more than 40 percent of the area of P. densiflora forest has been damaged already, however some individuals could escapes from the damage and contribute to restore the site to the previous vegetation composition. When the stands were attacked by this insect, the drastic openings of the upper story of tree canopy formed by exclusively P. densiflora are usually resulted and some environmental factors such as light, temperature, litter accumulation, soil moisture and offers were naturally modified. With these changes after insect invasion, as the time passes, phytosociologic changes of the vegetation are gradually proceeding. If we select the forest according to four categories concerning the history of the insect outbreak, namely, non-attacked (healthy forest), recently damaged (the outbreak occured about 1-2 years ago), severely damaged (occured 5-6 years ago), damage prolonged (occured 10 years ago) and restored (occured about 20 years ago), any directional changes of vegetation composition could be traced these in line with four progressive stages. To elucidate these changes, three survey districts; (1) "Gongju" where the damage was severe and it was outbroken in 1977, (2) "Buyeo" where damage prolonged and (3) "Gochang" as restored, were set, (See Tab. 1). All these were located in the south temperate forest zone which was delimited mainly due to the temporature factor and generally accepted without any opposition at present. In view of temperature, the amount and distribution of precipitation and various soil factor, the overall homogeneity of environmental conditions between survey districts might be accepted. However this did not mean that small changes of edaphic and topographic conditions and microclimates can induce any alteration of vegetation patterns. Again four survey plots were set in each district and inter plot distance was 3 to 4 km. And again four subplots were set within a survey plot. The size of a subplot was $10m{\times}10m$ for woody vegetation and $5m{\times}5m$ for ground cover vegetation which was less than 2 m high. The nested quadrat method was adopted. In sampling survey plots, the followings were taken into account: (1) Natural growth having more than 80 percent of crown density of upper canopy and more than 5 hectares of area. (2) Was not affected by both natural and artificial disturbances such as fire and thinning operation for the past three decades. (3) Lower than 500 m of altitude (4) Less than 20 degrees of slope, and (5) Northerly sited aspect. An intensive vegetation survey was undertaken during the summer of 1980. The vegetation was devided into 3 categories for sampling; the upper layer (dominated mainly by the pine trees), the middle layer composed by oak species and other broad-leaved trees as well as the pine, and the ground layer or the lower layer (shrubby form of woody plants). In this study our survey was concentrated on woody species only. For the vegetation analysis, calculated were values of intensity, frequency, covers, relative importance, species diversity, dominance and similarity and dissimilasity index when importance values were calculated, different relative weights as score were arbitrarily given to each layer, i.e., 3 points for the upper layer, 2 for the middle layer and 1 for the ground layer. Then the formula becomes as follows; $$R.I.V.=\frac{3(IV\;upper\;L.)+2(IV.\;middle\;L.)+1(IV.\;ground\;L.)}{6}$$ The values of Similarity Index were calculated on the basis of the Relative Importance Value of trees (sum of relative density, frequency and cover). The formula used is; $$S.I.=\frac{2C}{S_1+S_2}{\times}100=\frac{2C}{100+100}{\times}100=C(%)$$ Where: C = The sum of the lower of the two quantitative values for species shared by the two communities. $S_1$ = The sum of all values for the first community. $S_2$ = The sum of all values for the second community. In Tab. 3, the species composition of each plot by layer and by district is presented. Without exception, the species formed the upper layer of stands was Pinus densiflora. As seen from the table, the relative cover (%), density (number of tree per $500m^2$), the range of height and diameter at brest height and cone bearing tendency were given. For the middle layer, Quercus spp. (Q. aliena, serrata, mongolica, accutissina and variabilis) and Pinus densiflora were dominating ones. Genus Rhodedendron and Lespedeza were abundant in ground vegetation, but some oaks were involved also. (1) Gongju district The total of woody species appeared in this district was 26 and relative importance value of Pinus densiflora for the upper layer was 79.1%, but in the middle layer, the R.I.V. for Quercus acctissima, Pinus densiflora, and Quercus aliena, were 22.8%, 18.7% and 10.0%, respectively, and in ground vegetation Q. mongolica 17.0%, Q. serrata 16.8% Corylus heterophylla 11.8%, and Q. dentata 11.3% in order. (2) Buyeo district. The number of species enumerated in this district was 36 and the R.I.V. of Pinus densiflora for the uppper layer was 100%. In the middle layer, the R.I.V. of Q. variabilis and Q. serrata were 8.6% and 8.5% respectively. In the ground vegetative 24 species were counted which had no more than 5% of R.I.V. The mean R.I.V. of P.densiflora ( totaling three layers ) and averaging four plots was 57.7% in contrast to 46.9% for Gongju district. (3) Gochang-district The total number of woody species was 23 and the mean R.I.V. of Pinus densiflora was 66.0% showing greater value than those for two former districts. The next high value was 6.5% for Q. serrata. As the time passes since insect outbreak, the mean R.I.V. of P. densiflora increased as the following order, 46.9%, 57.7% and 66%. This implies that P. densiflora was getting back to its original dominat state again. The pooled importance of Genus Quercus was decreasing with the increase of that for Pinus densiflora. This trend was contradict to the facts which were surveyed at Kyonggi-do area (the central temperate forest zone) reported previously (Yim et al, 1980). Among Genus Quercus, Quercus acutissina, warm-loving species, was more abundant in the southern temperature zone to which the present research is concerned than the central temperate zone. But vice-versa was true with Q. mongolica, a cold-loving one. The species which are not common between the present survey and the previous report are Corpinus cordata, Beltala davurica, Wisturia floribunda, Weigela subsessilis, Gleditsia japonica var. koraiensis, Acer pseudosieboldianum, Euonymus japonica var. macrophylla, Ribes mandshuricum, Pyrus calleryana var. faruiei, Tilia amurensis and Pyrus pyrifolia. In Figure 4 and Table 5, Maximum species diversity (maximum H'), Species diversity (H') and Eveness (J') were presented. The Similarity indices between districts were shown in Tab. 5. Seeing Fig. 6, showing two-dimensional ordination of polts on the basis of X and Y coordinates, Ai plots aggregate at the left site, Bi plots at lower site, and Ci plots at upper-right site. The increasing and decreasing patterns as to Relative Density and Relative Importance Value by genus or species were given in Fig. 7. Some of the patterns presented here are not consistent with the previously reported ones (Yim, et al, 1980). The present authors would like to attribute this fact that two distinct types of the insect attack, one is the short war type occuring in the south temperate forest zone, which means that insect attack went for a few years only, the other one is a long-drawn was type observed at the temperate forest zone in which the insect damage went on continuously for several years. These different behaviours of infestation might have resulted the different ways of vegetational change. Analysing the similarity indices between districts, the very convincing results come out that the value of dissimilarity index between A and B was 30%, 27% between B and C and 35% between A and C (Table 6). The range of similarity index was obtained from the calculation of every possible combinations of plots between two districts. Longer time isolation between communities has brought the higher value of dissimilarity index. The main components of ground vegetation, 10 to 20 years after insect outbreak, become to be consisted of mainly Genus Lespedeza and Rhododendron. Genus Quercus which relate to the top dorminant state for a while after insect attack was giving its place to Pinus densiflora. It was implied that, provided that the soil fertility, soil moisture and soil depth were good enough, Genus Quercuss had never been so easily taken ever by the resistant speeies like Pinus densiflora which forms the edaphic climax at vast areas of forest land. Usually they refer Quercus to the representative component of the undisturbed natural forest in the central part of this country.

• Applied Biological Chemistry
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• v.6
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• pp.61-77
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• 1965

In this experiment, Akiochi was studied especially on plant growth on the degraded soils. Besides, such soils were carefully examined on its character and plant body was analysed to know the difference in various mineral contents. For this purpose, paddy cultivation was done with the variety Pal Dal at Suwon, Sosa and Pyungtak. Three plots were chosen at each location as the normal and 2 levels of akiochi, a-the stronger and b-the weaker. Harvests from these 9 plots were measured agronomically and also chemically analysised. As for soil, after an observation on vertical section of soil, samples from each layer were also studied both physically and chemically. The results are summarized as follows. 1. Outer changes in rice plant and changes in yield components. 1) Rice from Akiochi soil showed remarkably shortened culm length, head length, protrusoion length, blade length of boot leaf, and coleoptile length, compared with that from the normal paddy field. 2) There was a tendency for Akiochi rice to have more heads per plant. 3) Akiochi rice showed poorer intercalary growth of upper 3 internodes. The ratio of this upper internode length to total culm length was also smaller in this case. Consquently the ratio of lower internode length to total culm length became larger than that from normal peddy field. 4) Akiochi rice showed significantly fewer first spikelets and attached grains of head at main stem. 5) Maturing rate of both this main seem of whole plant body was remarkably lower than that of normal rice. 6) Akiochi rice showed lower head weight of main stem, total hulled rice weight, total grain yield, 1000-grain weight, straw weight and straw-hulled rice ratio. 2. Physical and chemical study on soil. 1) Akiochi soil showed thinner upper layer and total thickness of upper and lower parts was smaller than that of normal. 2) Akiochi soil of Suwon was mainly composed of sand, while that of Sosa and Pyungtak was composed of heavy clay. 3) Chemical analysis indicated that content of $SiO_2$ in upper layer is always lower than that of normal. But no other common tendencies were found. 4) This analysis further lillustrates lower content of Fe, & Mn at Suwon ; of Mn at Sosa and higher content of Fe at Sosa and organic matters at Pyungtak. 5) Some differences in the content of N in each plot could be marked though irregular. 3. Chemical Composition of plant body. 1) Chemical analysis on grain, boot leaf and straw did not suggest any remarkable differences between normal and Akiochi rice, except that the latter contains less Si in boot leaf and less Mn in straw. 2) Contents of each chemical element were measured in grain and straw to calculate the percentage of element content in grain to that of whole plant body including both grain and straw. Here, Akiochi rice always showed lower value in N, K and Mn. 4. Relationship between chemical composition of plant body and that of soil. Akiochi soil at Sosa marked lower content of Mn. This caused another lower content of this element in grain, boot leaf and straw. But except that, no remarkable relationship could be found in this study.