• Journal of People, Plants, and Environment
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• v.24 no.2
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• pp.219-227
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• 2021

Background and objective: Urban street trees play an important role in carbon reduction in cities where greenspace is scarce. There are ongoing studies on carbon reduction by street trees. However, information on the carbon reduction capacity of street trees based on field surveys is still limited. This study aimed to quantify carbon uptake and storage by urban street trees and suggest a method to improve planting of trees in order to increase their carbon reduction capacity. Methods: The cities selected were Sejong, Chungju, and Jeonju among cities without research on carbon reduction, considering the regional distribution in Korea. In the cities, 155 sample sites were selected using systematic sampling to conduct a field survey on street environments and planting structures. The surveyed data included tree species, diameter at breast height (DBH), diameter at root collar (DRC), height, crown width, and vertical structures. The carbon uptake and storage per tree were calculated using the quantification models developed for the urban trees of each species. Results: The average carbon uptake and storage of street trees were approximately 7.2 ± 0.6 kg/tree/yr and 87.1 ± 10.2 kg/tree, respectively. The key factors determining carbon uptake and storage were tree size, vertical structure, the composition of tree species, and growth conditions. The annual total carbon uptake and storage were approximately 1,135.8 tons and 22,737.8 tons, respectively. The total carbon uptake was about the same amount as carbon emitted by 2,272 vehicles a year. Conclusion: This study has significance in providing the basic unit to quantify carbon uptake and storage of street trees based on field surveys. To improve the carbon reduction capacity of street trees, it is necessary to consider planning strategies such as securing and extending available grounds and spaces for high-density street trees with a multi-layered structure.

• Journal of Environmental Science International
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• v.32 no.6
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• pp.429-440
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• 2023

Quantitative habitat model is established with species occurrence and spatial abundance data, which were usually acquired by professional field ecologists and citizen scientists. The importance of citizen science data is increasing, but the quality of these data needs to be evaluated. This study aims to identify and compare both expert-based data and citizen science data based on the performance power of quantitative models derived from both data sets. A Maximum Entropy (MaxENT) model was developed using eight environmental variables, including climate, topography, landcover and distance to forest edge. The AUC values derived from the MaxENT model were 0.842 and 0.809, respectively, indicating a high level of explanatory power. All environmental variables has similar values for both data sets, except for the distance to forest edge and rice paddy, which was relatively higher for expert-based survey data than that of the citizen science data as the distances increased. This result suggests that habitat model derived from expert-based survey data shows more ecological niche including wider ranges from forest edges and isolated habitat patches of rice paddy. This is presumably because citizen scientists focuses on direct observation methods, whereas professional field surveys investigate a wider variety of methods.

• Journal of Korean Society of Forest Science
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• v.100 no.3
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• pp.455-465
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• 2011

In order to assess and mitigate climate change, the role of forest biomass as carbon sink has to be understood spatially and quantitatively. Since existing forest statistics can not provide spatial information about forest resources, it is needed to predict spatial distribution of forest biomass under an alternative scheme. This study focuses on developing an upscaling method that expands forest variables from plot to landscape scale to estimate spatially explicit aboveground biomass(AGB). For this, forest stand variables were extracted from National Forest Inventory(NFI) data and used to develop AGB regression models by tree species. Dominant/codominant height and crown density were used as explanatory variables of AGB regression models. Spatial distribution of AGB could be estimated using AGB models, forest type map and the stand height map that was developed by forest type map and height regression models. Finally, it was estimated that total amount of forest AGB in Danyang was 6,606,324 ton. This estimate was within standard error of AGB statistics calculated by sample-based estimator, which was 6,518,178 ton. This AGB upscaling method can provide the means that can easily estimate biomass in large area. But because forest type map used as base map was produced using categorical data, this method has limits to improve a precision of AGB map.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.2
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• pp.79-88
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• 2015

Preparations need to be made for Korean pine(Pinus koraiensis) in anticipation of climate change because Korean pine is an endemic species of South Korea and the source of timber and pine nut. Therefore, climate change adaptation policy has been established to conduct an impact assessment on the distribution of Korean pine. Our objective was to predict the distribution of Korean pine while taking into account uncertainty and afforestation conditions. We used the 5th forest types map, a forest site map and BIOCLIM variables. The climate scenarios are RCP 4.5 and RCP 8.5 for uncertainty and the climate models are 5 regional climate models (HadGEM3RA, RegCM4, SNURCM, GRIMs, WRF). The base period for this study is 1971 to 2000. The target periods are the mid-21st century (2021-2050) and the end of the 21st century (2071-2100). This study used the MaxEnt model, and 50% of the presences were randomly set as training data. The remaining 50% were used as test data, and 10 cross-validated replicates were run. The selected variables were the annual mean temperature (Bio1), the precipitation of the wettest month (Bio13) and the precipitation of the driest month (Bio14). The test data's ROC curve of Korean pine was 0.689. The distribution of Korean pine in the mid-21st century decreased from 11.9% to 37.8% on RCP 4.5 and RCP 8.5. The area of Korean pine at an artificial plantation occupied from 32.1% to 45.4% on both RCPs. The areas at the end of the 21st century declined by 53.9% on RCP 4.5 and by 86.0% on RCP 8.5. The area of Korean pine at an artificial plantation occupied 23.8% on RCP 4.5 and 7.2% on RCP 8.5. Private forests showed more of a decrease than national forests for all subsequent periods. Our results may contribute to the establishment of climate change adaptation policies for considering various adaptation options.

• Journal of Korean Society of Forest Science
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• v.101 no.4
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• pp.599-605
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• 2012

The purpose of this study is to estimate diameter distribution, volume per hectare, and carbon stock for Quercus variabilis stand. 354 Quercus variabilis stands were selected on the basis of age and structure, the data and samples for these stands are collected. For the prediction of diameter distribution, Weibull model was applied and for the estimation of the parameters, a simplified method-of-moments was applied. To verify the accuracy of estimates, models were developed using 80% of the total data and validation was done on the remaining 20%. For the verification of the model, the fitness index, the root mean square error, and Kolmogorov-Smirnov statistics were used. The fitness index of the site index, height, and volume equation estimated from verification procedure were 0.967, 0.727, and 0.988 respectively and the root mean square error were 2.763, 1.817, and 0.007 respectively. The Kolmogorov-Smirnov test applied to Weibull function resulted in 75%. From the models developed in this research, the estimated volume and above-ground carbon stock were derived as $188.69m^3/ha$, 90.30 tC/ha when site index and stem number of 50-years-old Quercus variabilis stand show 14 and 697 respectively. The results obtained from this study may provide useful information about the growth of broad-leaf species and prediction of carbon stock for Quercus variabilis stand.

• Korean Journal of Environmental Biology
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• v.35 no.3
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• pp.413-425
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• 2017

This manuscript describes the relationship between climate change and forest growth, forest species, carbon stocks, and tree mortality. 1) In the aspect of forest growth, the growth of major coniferous species, including Pinus densiflora, had a negative correlation with temperature. On the other hand, major deciduous oak species, including Quercus variabilis and Quercus mongolica, had a positive correlation with temperature. 2) When considered in the aspect of the forest species distribution, various models commonly showed a decrease in the distribution of coniferous species and an increase in oak species due to climate change in the medium to long term. 3) From the carbon stock perspective, there was a difference in the estimation according to the status of forest management. Most of Korean forests will mature to become over-matured forest after year 2030 and are estimated to produce approximately 410 million ton forest biomass until 2090 with the current cutting regulations for sustainable forest management announced by the Korean Forest Service. 4) In the forest mortality, the mortality rate of the major coniferous species showed a clear tendency to increase higher temperatures while it decreased for the oak species with no verification of statistical significance. Moreover, the mortality of the subalpine coniferous species was projected to progress rapidly. considering the overall impacts described above, there should be a management strategy for coniferous species that are relatively vulnerable to climate change. Moreover, a sustainable forest plan in the aspect of ecosystem services, carbon sequestration and storage, which is linked to global issues such as Sustainable Development Goals, ecosystem services and negative emission.

• Journal of Ecology and Environment
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• v.41 no.11
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• pp.310-317
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• 2017

Background: Many studies about climate-related range shift of plants have focused on understanding the relationship between climatic factors and plant distributions. However, consideration of adaptation factors, such as dispersal and plant physiological processes, is necessary for a more accurate prediction. This study predicted the future distribution of marlberry (Ardisia japonica), a warm-adapted evergreen broadleaved shrub, under climate change in relation to the dispersal ability that is determined by elapsed time for the first seed production. Results: We introduced climate change data under four representative concentration pathway (RCP 2.6, 4.5, 6.0, and 8.5) scenarios from five different global circulation models (GCMs) to simulate the future distributions (2041~2060) of marlberry. Using these 20 different climate data, ensemble forecasts were produced by averaging the future distributions of marlberry in order to minimize the model uncertainties. Then, a dispersal-limited function was applied to the ensemble forecast in order to exam the impact of dispersal capacity on future marlberry distributions. In the dispersal-limited function, elapsed time for the first seed production and possible dispersal distances define the dispersal capacity. The results showed that the current suitable habitats of marlberry expanded toward central coast and southern inland area from the current southern and mid-eastern coast area in Korea. However, given the dispersal-limited function, this experiment showed lower expansions to the central coast area and southern inland area. Conclusions: This study well explains the importance of dispersal capacity in the prediction of future marlberry distribution and can be used as basic information in understanding the climate change effects on the future distributions of Ardisia japonica.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.348-357
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• 2015

The main purpose of this study is to understand the potential geographic distribution of P. koraiensis, which is known to be one of major economic tree species, based on the RCP (Representative Concentration Pathway) 8.5 scenarios and current geographic distribution from National Forest Inventory(NFI) data using ecological niche modeling. P. koraiensis abundance data extracted from NFI were utilized to estimate current geographic distribution. Also, GARP (Genetic Algorithm for Rule-set Production) model, one of the ecological niche models, was applied to estimate potential geographic distribution and to project future changes. Environmental explanatory variables showing Area Under Curve (AUC) value bigger than 0.6 were selected and constructed into the final model by running the model for each of the 27 variables. The results of the model validation which was performed based on confusion matrix statistics, showed quite high suitability. Currently P. koraiensis is distributed widely from 300m to 1,200m in altitude and from south to north as a result of national greening project in 1970s although major populations are found in elevated and northern area. The results of this study were successful in showing the current distribution of P. koraiensis and projecting their future changes. Future model for P. koraiensis suggest large areas predicted under current climate conditions may be contracted by 2090s showing dramatic habitat loss. Considering the increasing status of atmospheric $CO_2$ and air temperature in Korea, P. koraiensis seems to experience the significant decrease of potential distribution range in the future. The final model in this study may be used to identify climate change impacts on distribution of P. koraiensis in Korea, and a deeper understanding of its correlation may be helpful when planning afforestation strategies.

• The Journal of Fisheries Business Administration
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• v.40 no.2
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• pp.49-70
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• 2009

This study proviedes GARCH model(Bollerslev, 1986) to analyze the structural characteristics of price volatility in domestic aquacultural fish market of Korea. As a case study, flatfish and rock-fish are analyzed as major species with relatively high portion in an aspect of production volume among fish captured in Korea. For analyzing, this study uses daily market data (dating from Jan 1 2000 to June 30, 2008) published by the Noryangjin Fisheries Wholesale Market which is located in Seoul of Korea. This study performs normality test on trading volume and price volatility of flatfish and rock-fish as an advanced empirical approach. The normality test adopted is Jarque-Bera test statistic. As a result, first, a null hypothesis that "an empirical distribution follows normal distribution" was rejected in both fishes. The distribution of daily market data of them were not only biased toward positive(+) direction in terms of kurtosis and skewness, but also characterized by leptokurtic distribution with long right tail. Secondly, serial correlations were found in data on market trading volume and price volatility of two species during very long period. Thirdly, the results of unit root test and ARCH-LM test showed that all data of time series were very stationary and demonstrated effects of ARCH. These statistical characteristics can be explained as a reasonable ground for supporting the fitness of GARCH model in order to estimate conditional variances that reveal price volatility in empirical analysis. From empirical data analysis above, this study drew the following conclusions. First of all, from an empirical analysis on potential effects of seasonality and the day of week on price volatility of aquacultural fish, Monday effects were found in both species and Thursday and Friday effects were also found in flatfish. This indicates that Monday is effective in expanding price volatility of aquacultural fish market and also Monday has higher effects upon the price volatility of fish than other days of week have since it has more new information for weekend. Secondly, the empirical analysis led to a common conclusion that there was very high price volatility of flatfish and rock-fish. This points out that the persistency parameter($\lambda$), an index of possibility for current volatility to sustain similarly in the future, was higher than 0.8-equivalently nearly to 1-in both flatfish and rock-fish, which presents volatility clustering. Also, this study estimated and compared and model that hypothesized normal distributions in order to determine fitness of respective models. As a result, the fitness of GARCH(1, 1)-t model was better than model where the distribution of error term was hypothesized through-distribution due to characteristics of fat-tailed distribution, was also better than model, as described in the results of basic statistic analysis. In conclusion, this study has an important mean in that it was introduced firstly in Korea to investigate in price volatility of Korean aquacultural fishery products, although there was partially a limited of official statistic data. Therefore, it is expected that the results of this study will be useful as a reference material for making and assessing governmental policies. Also, it is looked forward that the results will be helpful to build a fishery business plan as and aspect of producer, and also to take timely measures to potential price fluctuations of fishery products in market. Hence, it is advisable that further studies related to such price volatility in fishery market will extend and evolve into a wider variety of articles and issues in near future.

• Journal of Korean Society of Forest Science
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• v.90 no.2
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• pp.176-183
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• 2001

Loblolly pine (Pinus taeda L.) is the most economically important timber producing species in the southern United States. Much attention has been given to predicting diameter distributions for the solution of multiple-product yield estimates. The three-parameter Weibull diameter distribution yield prediction systems were developed for loblolly pine plantations. A parameter recovery procedure for the Weibull distribution function based on four percentile equations was applied to develop diameter distribution yield prediction models. Four percentiles (0th, 25th, 50th, 95th) of the cumulative diameter distribution were predicted as a function of quadratic mean diameter. Individual tree height prediction equations were developed for the calculation of yields by diameter class. By using individual tree content prediction equations, expected yield by diameter class can be computed. To reduce rounding-off errors, the Weibull cumulative upper bound limit difference procedure applied in this study shows slightly better results compared with upper and lower bound procedure applied in the past studies. To evaluate this system, the predicted diameter distributions were tested against the observed diameter distributions using the Kolmogorov-Smirnov two sample test at the ${\alpha}$=0.05 level to check if any significant differences existed. Statistically, no significant differences were detected based on the data from 516 evaluation data sets. This diameter distribution yield prediction system will be useful in loblolly pine stand structure modeling, in updating forest inventories, and in evaluating investment opportunities.