• The Korean Journal of Ecology
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• v.26 no.4
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• pp.199-202
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• 2003

According to the energy hypothesis, the energy input per unit area primarily determines species richness in regions of roughly equal area. Some energy-related ecological research included identification of major climatic variables to determine regional species richness. In this study, the local butterfly species richness was examined to find out whether weather variables affected the local distribution or abundance of butterfly populations. Butterfly monitoring data from May 2001 to April 2002 taken at Mt. Yudal, Mokpo, in the southwestern part of Korea, and six weather variables (monthly mean values of temperature, precipitation, evaporation, wind speed, air pressure, and sunlight) were analyzed. Multiple regression analysis showed that only temperature explained 80% and 70% of the variability of log-transformed number of species and individuals, respectively, indicating that temperature played an important role in local species richness. Furthermore, global warming could affect the abundance and distribution of butterflies regionally as well as locally.

• Textile Coloration and Finishing
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• v.20 no.4
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• pp.21-30
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• 2008

To understand the complex hydrogen bonding structure, several phenolic derivatives and benzoxazine model compounds are synthesized and characterized by Fourier transform infrared spectroscopy (FT-IR). The estimation of molar extinction coefficients for various types of hydrogen bonding species is systematically carried out by the curve-resolving of FT-IR spectra. The distribution of hydrogen bonding species in benzoxazine model dimers is quantitatively analyzed. It is revealed that benzoxazine dimers and BA-a polybenzoxazine are mainly composed of intramolecular interaction rather than intermolecular interaction.

• Journal of Environmental Impact Assessment
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• v.21 no.5
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• pp.735-743
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• 2012

Since the CBD(Conservation on Biological Diversity)'s 10th Conference of the Parties adopted the protocol on access to genetic resources and benefit sharing in Nagoya 2010, the importance of endangered species studies such as habitat distribution, protection and management have been more emerged. Corylopsis coreana, an endangered species in Korea, was isolated nationally and has been damaged by anthropogenic factors. In this paper, we identified the factors affecting C. coreana habitat at the national scale and regional scale using National Survey of Natural Environment and predicted the distribution of C. coreana. Annual precipitation, precipitation of wettest quarter, temperature seasonality and Digital Elevation Model(DEM) were derived as important factors at the national scale, and precipitation of wettest quarter, DEM and solar radiation on spring were identified as important factors at regional scale. Colylopsis distribution was affected by an effect of climate significantly at the national scale, and by additionally the microclimate and topography at regional scale. These findings will be used as the basis on habitat conservation and restoration plan and climate change.

• Korean Journal of Environmental Biology
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• v.40 no.2
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• pp.214-223
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• 2022

Among migratory insect pests, Mythimna seperata and Cnaphalocrocis medinalis are invasive pests introduced into South Korea through westerlies from southern China. M. seperata and C. medinalis are insect pests that use rice as a host. They injure rice leaves and inhibit rice growth. To understand the distribution of M. seperata and C. medinalis, it is important to understand environmental factors such as temperature and humidity of their habitat. This study predicted current and future habitat suitability models for understanding the distribution of M. seperata and C. medinalis. Occurrence data, SSPs (Shared Socio-economic Pathways) scenario, and RCP (Representative Concentration Pathway) were applied to MaxEnt (Maximum Entropy), a machine learning model among SDM (Species Distribution Model). As a result, M. seperata and C. medinalis are aggregated on the west and south coasts where they have a host after migration from China. As a result of MaxEnt analysis, the contribution was high in the order of Land-cover data and DEM (Digital Elevation Model). In bioclimatic variables, BIO_4 (Temperature seasonality) was high in M. seperata and BIO_2 (Mean Diurnal Range) was found in C. medinalis. The habitat suitability model predicted that M. seperata and C. medinalis could inhabit most rice paddies.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.6
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• pp.135-149
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• 2015

Korean fir(Abies koreana E.H.Wilson 1920), endemic tree species of Korean peninsula, is considered as vulnerable and endangered species to recent rapid environmental changes such as land use and climate change. There are limited activities and efforts to find natural habitats of Korean fir for conservation of the species and habitats. In this study, by applying SDMs (Species Distribution Models) based on climate and topographic factors of Korean fir, we developed Korean fir's predicted distribution model and explored novel natural habitats. In Mt. Shinbulsan, Youngnam region and Mt. Songnisan, we could find korean fir's two novel habitat and the former was the warmest($13^{\circ}C$ in annual mean temperature), the driest(1,200mm~1,600mm in annual rainfall) and relatively low altitude environment among Korean fir's habitats in Korea. The result of SDMs did not include mountain areas of Gangwon-do as habitats of A. nephrolepis, because there were different contributions of key habitat environment factors, summer rainfall, winter mean temperature and winter rainfall, between A. koreana and A. nephrolepis. Our results raise modification of other distribution models on Korean fir. Novel habitat of Korean fir in Mt. Shinbulsan revealed similar habitat affinity of the species, ridgy and rocky site, with other habitats in Korea. Our results also suggest potential areas for creation of Korea fir's alternative habitats through species reintroduction in landscape and ecosystem level.

• Journal of Species Research
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• v.10 no.3
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• pp.246-254
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• 2021

Subalpine and alpine ecosystems are especially vulnerable to temperature increases. Betula ermanii Cham. (Betulaceae) is a dominant broad-leaved tree species in the subalpine zone and is designated as a 'Climate-sensitive Biological Indicator Species' in South Korea. This study aimed to predict the potential distribution of B. ermanii under current and future climate conditions in South Korea using the MaxEnt model. The species distribution models showed an excellent fit (AUC=0.99). Among the climatic variables, the most critical factors shaping B. ermanii distribution were identified as the maximum temperature of warmest month (Bio5; 64.8%) and annual mean temperature (Bio1; 20.3%). Current potential habitats were predicted in the Baekdudaegan mountain range and Mt. Hallasan, and the area of suitable habitat was 1531.52 km², covering 1.57% of the Korean Peninsula. With global warming, future climate scenarios have predicted a decrease in the suitable habitats for B. ermanii. Under RCP8.5-2070s, in particular, habitat with high potential was predicted only in several small areas in Gangwon-do, and the total area suitable for the species decreased by up to 97.3% compared to the current range. We conclude that the dominant factor affecting the distribution of B. ermanii is temperature and that future temperature rises will increase the vulnerability of this species.

• Journal of Climate Change Research
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• v.7 no.3
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• pp.325-334
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• 2016

We projected the distribution of Hedera rhombea, an evergreen broad-leaved climbing plant, under current climate conditions and predicted its future distributions under global warming. Inaddition, weexplained model uncertainty by employing 9 single Species Distribution model (SDM)s to model the distribution of Hedera rhombea. 9 single SDMs were constructed with 736 presence/absence data and 3 temperature and 3 precipitation data. Uncertainty of each SDM was assessed with TSS (Ture Skill Statistics) and AUC (the Area under the curve) value of ROC (receiver operating characteristic) analyses. To reduce model uncertainty, we combined 9 single SDMs weighted by TSS and resulted in an ensemble forecast, a TSS weighted ensemble. We predicted future distributions of Hedera rhombea under future climate conditions for the period of 2050 (2040~2060), which were estimated with HadGEM2-AO. RF (Random Forest), GBM (Generalized Boosted Model) and TSS weighted ensemble model showed higher prediction accuracies (AUC > 0.95, TSS > 0.80) than other SDMs. Based on the projections of TSS weighted ensemble, potential habitats under current climate conditions showed a discrepancy with actual habitats, especially in the northern distribution limit. The observed northern boundary of Hedera rhombea is Ulsan in the eastern Korean Peninsula, but the projected limit was eastern coast of Gangwon province. Geomorphological conditions and the dispersal limitations mediated by birds, the lack of bird habitats at eastern coast of Gangwon Province, account for such discrepancy. In general, potential habitats of Hedera rhombea expanded under future climate conditions, but the extent of expansions depend on RCP scenarios. Potential Habitat of Hedera rhombea expanded into Jeolla-inland area under RCP 4.5, and into Chungnam and Wonsan under RCP 8.5. Our results would be fundamental information for understanding the potential effects of climate change on the distribution of Hedera rhombea.

• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.410-419
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• 2018

Purpose: CLIMEX, a species distribution modeling tool, includes various types of parameters representing climatic conditions; the estimation of these parameters directly determines the model accuracy. In this study, we investigated the sensitivity of parameters for the climatic suitability calculated by CLIMEX for Metcalfa pruinosa in South Korea. Methods: We first changed 12 parameters and identified the three significant parameters that considerably affected the CLIMEX simulation response. Results: The result indicated that the simulation was highly sensitive to changes in lower optimal temperatures, lower soil moisture thresholds, and cold stress accumulation rate based on the sensitivity index, suggesting that these were the fundamental parameters to be used for fitting the simulation into the actual distribution. Conclusion: Sensitivity analysis is effective for estimating parameter values, and selecting the most important parameters for improving model accuracy.

• Journal of Forest and Environmental Science
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• v.31 no.3
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• pp.207-213
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• 2015

It is estimated that there is a total of approximately 100,000 species in Korea. However, the number is currently about 30,000 and only 16,027 species are listed in the 'Species Korea' (as of December, 2014). Of the listed species, 51 species are designated as the Endangered Species Class I while 195 species are in the Class II, totaling 246 endangered species including 20 mammals. Under the circumstances that development (e.g., roads) is increasingly threatening the persistence of endangered mammals, it is significant to identify and preserve suitable habitats for them. In this context, evaluating the values of the suitable habitat environment would serve as essential information for development decision making. This study estimated the values of endangered mammals' forest habitats through spatialization of habitat services. In doing so, a species distribution model, Maximum Entropy Model (MaxEnt) was utilized for a group of endangered mammals including, mountain goat, wildcat, marten cat, and flying squirrel. To calculate the values per unit area, a benefit transfer method was used based on the point-estimate technique with the best available values estimated previously. The range of discount rate of 3.0 to 5.5 percent was applied taking the notion of social discount rate into account. As a result, the province with the highest values for endangered mammal habitats appeared to be Gangwon, followed by Gyeongbuk and Gyeongnam. The monetary values of the endangered mammal habitats were estimated to be 330 billion to 421 billion won per year.

• Journal of Ecology and Environment
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• v.43 no.2
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• pp.191-201
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• 2019

Macroecologists and biogeographers continue to predict the distribution of species across space based on the relationship between biotic processes and environmental variables. This approach uses data related to, for example, species abundance or presence/absence, climate, geomorphology, and soils. Researchers have acknowledged in their statistical analyses the importance of accounting for the effects of spatial autocorrelation (SAC), which indicates a degree of dependence between pairs of nearby observations. It has been agreed that residual spatial autocorrelation (rSAC) can have a substantial impact on modeling processes and inferences. However, more attention should be paid to the sources of rSAC and the degree to which rSAC becomes problematic. Here, we review previous studies to identify diverse factors that potentially induce the presence of rSAC in macroecological and biogeographical models. Furthermore, an emphasis is put on the quantification of rSAC by seeking to unveil the magnitude to which the presence of SAC in model residuals becomes detrimental to the modeling process. It turned out that five categories of factors can drive the presence of SAC in model residuals: ecological data and processes, scale and distance, missing variables, sampling design, and assumptions and methodological approaches. Additionally, we noted that more explicit and elaborated discussion of rSAC should be presented in species distribution modeling. Future investigations involving the quantification of rSAC are recommended in order to understand when rSAC can have an adverse effect on the modeling process.