• Journal of Environmental Impact Assessment
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• v.31 no.4
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• pp.214-225
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• 2022

This study emphasized the soil of environmental impact assessment to devise measures to minimize the negative impact of project implementation on the environment. As a series of efforts for impact assessment procedures, a national inventory-based database was established for urban development projects, and three machine learning model performance evaluation as well as soil pollutant concentration distribution mapping were conducted. Here, nine soil pollutants were mapped to the metropolitan area of South Korea using the Random Forest model, which showed the best performance. The results of this study found that concentrations of Zn, F, and Cd were relatively concerned in Seoul, where urbanization is the most active. In addition, in the case of Hg and Cr6+, concentrations were detected below the standard, which was derived from a lack of pollutants such as industrial and industrial complexes that affect contents of heavy metals. A significant correlation between land cover and pollutants was inferred through the spatial distribution mapping of soil pollutants. Through this, it is expected that efficient soil management measures for minimizing soil pollution and planning decisions regarding the location of the project site can be established.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.4
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• pp.49-65
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• 2022

Since trees in the city are green assets that create a healthy environment for the city, systematic management of trees improves urban ecosystem services. The sporadic urban tree information centered on the site is vast, and it is difficult to manage the data, so efforts to increase efficiency are needed. This paper summarizes tree data inventory based on data constructed by Seoul Green Trust activists and constructs and discloses online database maps using Tableau Software. In order to verify the utilization of the map, we divided into consumer and supplier aspects to collect various opinions and reflect feedback to implement tree database maps for each area and species of Seoul Forest. As a result, the utilization value of tree database in urban parks was presented. The technical significance of this study is to systematically record the process of constructing and implementing a dashboard directly using the Mapbox platform and Tableau Software in the field of landscaping for the first time in Korea. In addition, the implications and supplements of landscape information were derived by collecting user opinions on the results. This can be used as an exploratory basis in the process of developing online-based services such as web and apps by utilizing landscaping tree information in the future. Although the visualization database currently constructed has limitations that ordinary users cannot interact in both directions because it utilizes business intelligence tools in terms of service provision it has affirmed both the database construction and its usability in web public format. In the future it is essential to investigate the assets of the trees in the city park and to build a database as a public asset of the city. The survey participants positively recognized that information is intuitively presented based on the map and responded that it is necessary to provide information on the overall urban assets such as small parks and roadside trees by using open source maps in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.55-67
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• 2021

Hornbeams (Carpinus spp.), which are widely distributed in South Korea, are recognized as one of the most abundant species at climax stage in the temperate forests. Although the distribution and vegetation structure of the C. laxiflora community have been reported, little ecological information of C. tschonoskii is available. Little effort was made to examine the distribution shift of these species under the future climate conditions. This study was conducted to predict potential shifts in the distribution of C. laxiflora and C. tschonoskii in 2050s and 2090s under the two sets of climate change scenarios, RCP4.5 and RCP8.5. The MaxEnt model was used to predict the spatial distribution of two species using the occurrence data derived from the 6th National Forest Inventory data as well as climate and topography data. It was found that the main factors for the distribution of C. laxiflora were elevation, temperature seasonality, and mean annual precipitation. The distribution of C. tschonoskii, was influenced by temperature seasonality, mean annual precipitation, and mean diurnal rang. It was projected that the total habitat area of the C. laxiflora could increase by 1.05% and 1.11% under RCP 4.5 and RCP 8.5 scenarios, respectively. It was also predicted that the distributional area of C. tschonoskii could expand under the future climate conditions. These results highlighted that the climate change would have considerable impact on the spatial distribution of C. laxiflora and C. tschonoskii. These also suggested that ecological information derived from climate change impact assessment study can be used to develop proper forest management practices in response to climate change.

• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.101-113
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• 1995

The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.

• Asia pacific journal of information systems
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• v.22 no.3
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• pp.53-74
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• 2012

A challenge in fostering virtual communities is the continuous supply of knowledge, namely members' willingness to contribute knowledge to their communities. Previous research argues that giving away knowledge eventually causes the possessors of that knowledge to lose their unique value to others, benefiting all except the contributor. Furthermore, communication within virtual communities involves a large number of participants with different social backgrounds and perspectives. The establishment of mutual understanding to comprehend conversations and foster knowledge contribution in virtual communities is inevitably more difficult than face-to-face communication in a small group. In spite of these arguments, evidence suggests that individuals in virtual communities do engage in social behaviors such as knowledge contribution. It is important to understand why individuals provide their valuable knowledge to other community members without a guarantee of returns. In virtual communities, knowledge is inherently rooted in individual members' experiences and expertise. This personal nature of knowledge requires social interactions between virtual community members for knowledge transfer. This study employs the social capital theory in order to account for interpersonal relationship factors and identity theory for individual and group factors that may affect knowledge contribution. First, social capital is the relationship capital which is embedded within the relationships among the participants in a network and available for use when it is needed. Social capital is a productive resource, facilitating individuals' actions for attainment. Nahapiet and Ghoshal (1997) identify three dimensions of social capital and explain theoretically how these dimensions affect the exchange of knowledge. Thus, social capital would be relevant to knowledge contribution in virtual communities. Second, existing research has addressed the importance of identity in facilitating knowledge contribution in a virtual context. Identity in virtual communities has been described as playing a vital role in the establishment of personal reputations and in the recognition of others. For instance, reputation systems that rate participants in terms of the quality of their contributions provide a readily available inventory of experts to knowledge seekers. Despite the growing interest in identities, however, there is little empirical research about how identities in the communities influence knowledge contribution. Therefore, the goal of this study is to better understand knowledge contribution by examining the roles of social capital and identity in virtual communities. Based on a theoretical framework of social capital and identity theory, we develop and test a theoretical model and evaluate our hypotheses. Specifically, we propose three variables such as cohesiveness, reciprocity, and commitment, referring to the social capital theory, as antecedents of knowledge contribution in virtual communities. We further posit that members with a strong identity (self-presentation and group identification) contribute more knowledge to virtual communities. We conducted a field study in order to validate our research model. We collected data from 192 members of virtual communities and used the PLS method to analyse the data. The tests of the measurement model confirm that our data set has appropriate discriminant and convergent validity. The results of testing the structural model show that cohesion, reciprocity, and self-presentation significantly influence knowledge contribution, while commitment and group identification do not significantly influence knowledge contribution. Our findings on cohesion and reciprocity are consistent with the previous literature. Contrary to our expectations, commitment did not significantly affect knowledge contribution in virtual communities. This result may be due to the fact that knowledge contribution was voluntary in the virtual communities in our sample. Another plausible explanation for this result may be the self-selection bias for the survey respondents, who are more likely to contribute their knowledge to virtual communities. The relationship between self-presentation and knowledge contribution was found to be significant in virtual communities, supporting the results of prior literature. Group identification did not significantly affect knowledge contribution in this study, inconsistent with the wealth of research that identifies group identification as an important factor for knowledge sharing. This conflicting result calls for future research that examines the role of group identification in knowledge contribution in virtual communities. This study makes a contribution to theory development in the area of knowledge management in general and virtual communities in particular. For practice, the results of this study identify the circumstances under which individual factors would be effective for motivating knowledge contribution to virtual communities.

• Strategy21
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• s.34
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• pp.58-92
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• 2014

Even after S. Korea took 5.24 Measure(24 May 2014), N. Korea has not stopped raising provocations such as the shelling of Yeonpyeong Island, electronic and cyber attacks. To make matters worse, the communist country lunched long-range missiles(twice) and conducted 3rd nuclear test, escalating tensions which could possibly lead to an all-out war. Korean Government failed to respond properly. However, escalation into an all-out war was deterred by the CFC immediately carrying out its peacetime duty(CODA). The US made a rapid dispatch of its augmentation forces(Aircraft carrier, nuclear-powered submarine, strategic bomber, F-22) to the Korean Peninsula. In recognition of the importance of the Combined Forces Command, since May 2013 the Park Geun-Hye Administration has been pushing ahead with re-postponement of Wartime Operational Control Transfer(which initially meant the disassembling of the CFC as of 1 December 2015) More recently, there has been a series of unusual indicators from the North. Judging from its inventory of 20 nuclear weapons, 1,000 ballistic missiles and biochemical weapons, it is safe to say that N. Korea has gained at least war deterrence against S. Korea. Normally a nation with nuclear weapons shrink its size of conventional forces, but the North is pursuing the opposite, rather increasing them. In addition, there was a change of war plan by N. Korea in 2010, changing 'Conquering the Korean Peninsula' to 'Negotiation after the seizure of the Greater Seoul Metropolitan Area(GSMA)' and establishing detailed plans for wartime projects. The change reflects the chain reaction in which requests from pro-north groups within the South will lead to the proclamation of war. Kim, Jeong-Un, leader of N. Korean regime, sent threatening messages using words such as 'exercising a nuclear preemptive strike right' and 'burning of Seoul'. Nam, Jae-June, Director of National Intelligence Service, stated that Kim, Jung-Un is throwing big talks, saying communization of the entire Korean Peninsula will come within the time frame of 3 years. Kim, Gwan-Jin, Defense Minister, shared an alarming message that there is a high possibility that the North will raise local provocations or a full-fledged war whenever while putting much emphasis on defense posture. As for the response concept of the Korean Government, it has been decided that 'ROK·US Combined Local Provocation Counter-Measure' will be adopted to act against local provocations from the North. Major provocation types include ▲ violation of the Northern Limit Line(NLL) with mobilization of military ships ▲ artillery provocations on Northwestern Islands ▲ low altitude airborne intrusion ▲ rear infiltration of SOF ▲ local conflicts within the Military Demarcation Line(MDL) ▲ attacking friendly ships by submarines. Counter-measures currently established by the US involves the support from USFK and USFJ. In order to keep the sworn promise, the US is reinforcing both USFK and USFJ. An all-out war situation will be met by 'CFC OPLAN5027' and 'Tailored Expansion Deterrence Forces' with the CFC playing a central role. The US augmentation forces stands at 690,000 troops, some 160 ships, 2,000 aircraft and this comprise 50% of US total forces, which is estimated to be ninefold of Korean forces. The CFC needs to be in center in handling both local provocations and an all-out war situation. However, the combat power of S. Korean conventional forces is approximately around 80% of that of N. Korea, which has been confirmed from comments made by Kim, Gwan-Jin, Defense Minister, during an interpellation session at the National Assembly. This means that S. Korean forces are not much growing. In particular, asymmetric capabilities of the North is posing a serious threat to the South including WMD, cyber warfare forces, SOF, forces targeting 5 Northwestern Islands, sub-surface and amphibious assault forces. The presence of such threats urgently requires immediate complementary efforts. For complementary efforts, the Korean Government should consider ① reinforcement of Korean forces; putting a stoppage to shrinking military, acquisition of adequate defense budget, building a missile defense and military leadership structure validity review, ② implementation of military tasks against the North; disciplinary measures on the sinking of ROKS Cheon-an/shelling of Yeonpyeong Islands, arrangement of inter-Korean military agreements, drawing lessons from studies on the correlation between aid for N. Korea, execution of inter-Korean Summit and provocations from the North, and ③ bolstering the ROK·US alliance; disregarding wartime operational control transfer plan(disassembling of CFC) and creation of a combined division.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.5
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• pp.705-715
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• 2010

The adoption of carbon foot print system is being activated mostly in the developed countries as one of the long-term response towards tightened up regulations and standards on carbon emission in the agricultural sector. The Korean Ministry of Environment excluded the primary agricultural products from the carbon foot print system due to lack of LCI (life cycle inventory) database in agriculture. Therefore, the research on and establishment of LCI database in the agriculture for adoption of carbon foot print system is urgent. Development of LCA (life cycle assessment) methodology for application of LCA to agricultural environment in Korea is also very important. Application of LCA methodology to agricultural environment in Korea is an early stage. Therefore, this study was carried out to find out the effect of lettuce cultivation on agricultural environment by establishing LCA methodology. Data collection of agricultural input and output for establishing LCI was carried out by collecting statistical data and documents on income from agro and livestock products prepared by RDA. LCA methodology for agriculture was reviewed by investigating LCA methodology and LCA applications of foreign countries. Results based on 1 kg of lettuce production showed that inputs including N, P, organic fertilizers, compound fertilizers and crop protectants were the main sources of major emission factor during lettuce cropping process. The amount of inputs considering the amount of active ingredients was required to estimate the actual quantity of the inputs used. Major emissions due to agricultural activities were $N_2O$ (emission to air) and ${NO_3}^-$/${PO_4}^-$ (emission to water) from fertilizers, organic compounds from pesticides and air pollutants from fossil fuel combustion in using agricultural machines. The softwares for LCIA (life cycle impact assessment) and LCA used in Korea are 'PASS' and 'TOTAL' which have been developed by the Ministry of Knowledge Economy and the Ministry of Environment. However, the models used for the softwares are the ones developed in foreign countries. In the future, development of models and optimization of factors for characterization, normalization and weighting suitable to Korean agricultural environment need to be done for more precise LCA analysis in the agricultural area.

• Journal of Korean Society of Forest Science
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• v.98 no.6
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• pp.772-779
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• 2009

This study was conducted to estimate the carbon (C) contents in pure and mixed stands of pine (Pinus densiflora) and oak (Quercus spp.) trees for establishing the C inventory of forest ecosystems. A total of fifteen 20 m${\times}$20 m pure and mixed stands of pine and oak trees were chosen in natural forests in Hoengseong, Kangwon based on the basal area of all trees ${\geq}$ 5 cm DBH: three of 95% of pine and 5% oak trees [pine stand], three of 100% of oak trees [oak stand], and nine of 20 to 70% of pine and 80 to 30% of oak trees [mixed stand]. To estimate C contents in the study stands, biomass in vegetation, forest floor and coarse woody debris (CWD) were calculated and C concentrations in vegetation, forest floor, CWD and soil (0-30 cm) were analyzed. There was no significant difference in vegetation C contents among the stands; 147.6 Mg C/ha for the oak stand, 141.4 Mg C/ha for the pine stand and 115.8 Mg C/ha for the mixed stand. Forest floor C contents were significantly different among the stands (p<0.05); 12.7 Mg/ha for the pine stand, 9.9 Mg/ha for the oak stand, and 8.4 Mg/ha for the mixed stand. However, CWD C contents were not significantly different among the stands (p>0.05); 2.2 Mg/ha for the mixed stand, 1.7 Mg/ha for the oak stand, and 1.1 Mg/ha for the pine stand. Soil C contents up to 30 cm depth were not significantly different among the study stands; 44.4 Mg C/ha for the pine stand, 41.6 Mg C/ha for the mixed stand, and 33.3 Mg C/ha for the oak stand. Total ecosystem C contents were lower in the mixed stand than those in the pure stands, because vegetation C contents which occupied almost total ecosystem C contents were lower in the mixed stand than those in the pure stands; 199.6 Mg C/ha for the pine stand, 192.5 Mg C/ha for the oak stand and 169.1 Mg C/ha for the mixed stand. Lower vegetation C contents in the mixed stand might be influenced by interspecific competition between pine and oak trees and intraspecific competition among the oak trees resulted from high stand density. We suggest that forest management such as thinning to enhance C storage is indispensible for minimizing the competition in forest ecosystems.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.5
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• pp.64-72
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• 2014

This study quantified the storage and annual uptake of carbon by apple trees in orchards as a production-type greenspace, and computed the annual carbon emissions from apple cultivation. Tree individuals in the study orchards were sampled to include the range of stem diameter sizes. The study measured biomass for each part including the roots of sample trees through a direct harvesting method to compute total carbon storage per tree. Annual carbon uptake per tree was quantified by analyzing the radial growth rates of stem samples at ground level. Annual carbon emissions from management practices such as pruning, mowing, irrigation, fertilization, and use of pesticides and fungicides were estimated based on maintenance data, interviews with managers, and actual measurements. Regression models were developed using stem diameter at ground level (D) as an independent variable to easily estimate storage and annual uptake of the carbon. Storage and annual uptake of carbon per tree increased as D sizes got larger. Apple trees with D sizes of 10 and 15 cm stored 9.1 and 21.0 kg of carbon and annually sequestered 1.0 and 1.6 kg, respectively. Storage and annual uptake of carbon per unit area in study orchards were 3.81 t/ha and 0.42 t/ha/yr, respectively, and annual carbon emissions were 1.30 t/ha/yr. Thus, the carbon emissions were about 3 times greater than the annual carbon uptake. The study identified management practices to reduce the carbon footprint of production-type greenspace, including efficient uses of water, pesticides, fungicides, and fertilizers. It breaks new ground by including measured biomass of roots and a detailed inventory of carbon emissions.

• Korean journal of applied entomology
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• v.49 no.4
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• pp.313-324
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• 2010

With growing interest in biodiversity in rice paddies, efficient sampling methods for quantitative evaluation of aquatic macroinvertebrates are needed because of their important role in rice paddies' food webs. For this reason, we sought a proper sampling method through comparing data collected by using aquatic net, quadrat, and core in rice paddies located in Chuncheon-si, Kangwon-do, Hongseong-gun, and Chungcheongnam-do. Because the frame of the net was rectangular and had a flat bottom, the area, sampledwith the aquatic net, was calculated by multiplying the net width by the sweeping length, All samples were taken from the space between the rows of rice plants. Twenty four taxa of macro invertebrates were collected in Chuncheon and 28 taxa in Hongseong. In Chuncheon, the number of taxa was similar among three sampling methods (17-18 taxa), but the number of individuals was different (aquatic net, $1,317/m^2$; quadrat, $1,368/m^2$; core, $1,810/m^2$. In Hongseong, the number of taxa sampled by aquatic net was the highest (aquatic net, 25 taxa; quadrat, 21 taxa; core, 16 taxa), but the core was the highest in the number of individuals (aquatic net, $1,586/m^2$; quadrat, $2,595/m^2$; core, $3,704/m^2$. The efficiency of samplers differed among taxa. Most of aquatic insect taxa were more abundant in the aquatic net, while those living on or in the paddy substratum such as Oligochaeta and Chironomidae were collected more in the quadrat sampler. To collect quantitative data for aquatic insects as well as to produce inventory of rare taxa, we suggest, based on samplers used in this study, to take quantitative samples of 6 replications from each of the edge and inner zones of a rice paddy by using an aquatic net, and to take qualitative samples both from sides of levees and the inner zone of rice paddy by using an aquatic net.