• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.215-231
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• 2020

Forest landscape models (FLMs) can be used to investigate the complex interactions of various ecological processes and patterns, which makes them useful tools to evaluate how environmental and anthropogenic variables can influence forest ecosystems. However, due to the large spatio-temporal scales in FLMs studies, parameterization and validation can be extremely challenging when applying to new study areas. To address this issue, we focused on the parameterization and application of a spatially explicit forest landscape model, LANDIS-II, to Mt. Gyebang, South Korea, with the use of the National Forest Inventory (NFI) and long-term ecological research (LTER) site data. In this study, we present the followings for the biomass succession extension of LANDIS-II: 1) species-specific and spatial parameters estimation for the biomass succession extension of LANDIS-II, 2) calibration, and 3) application and validation for Mt. Gyebang. For the biomass succession extension, we selected 14 tree species, and parameterized ecoregion map, initial community map, species growth characteristics. We produced ecoregion map using elevation, aspect, and topographic wetness index based on digital elevation model. Initial community map was produced based on NFI and sub-alpine survey data. Tree species growth parameters, such as aboveground net primary production and maximum aboveground biomass, were estimated from PnET-II model based on species physiological factors and environmental variables. Literature data were used to estimate species physiological factors, such as FolN, SLWmax, HalfSat, growing temperature, and shade tolerance. For calibration and validation purposes, we compared species-specific aboveground biomass of model outputs and NFI and sub-alpine survey data and calculated coefficient of determination (R²) and root mean square error (RMSE). The final model performed very well, with 0. 98 R² and 8. 9 RMSE. This study can serve as a foundation for the use of FLMs to other applications such as comparing alternative forest management scenarios and natural disturbance effects.

• Korean Journal of Environmental Biology
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• v.37 no.1
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• pp.19-30
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• 2019

To investigate the characteristics of seasonal environment and phytoplankton community structure in the coastal area of Dokdo, a survey of Dokdo around waters was conducted during the four seasons. Phytoplankton of 4 phylum 72 species in four seasons were collected in Dokdo around water. The seasonal mean abundance of phytoplankton were $3.32{\times}10^4cells\;L^{-1}$ in winter, $1.04{\times}10^4cells\;L^{-1}$ in spring, $0.28{\times}10^4cells\;L^{-1}$ in summer, and $4.86{\times}10^4cells\;L^{-1}$ in autumn in Dokdo around water. During winter, the diatoms Chaetoceros spp. had dominated. During spring, when the nutrients in the euphotic layer were depleted, the nano-flagellates and Cryptomonas appeared at surface layer. In summer, the abundance of phytoplankton was relatively low, which lead to occurrence of diatoms such as genus of Chaetoceros, Rhizosolenia, and Skeletonema. In autumn, Pseudo-nitzschia spp. was the most dominant species and tropical species such as Amphisolenia sp. and Ornithocercus magnificus were observed, implying that they may have introduced within warm water current such as Kurosiwo Current. Therefore, although natural phytoplankton communities in the vicinity water of Dokdo are mainly influenced by Tsushima Warm Current branched Kurosiwo Current, their population dynamics was affected on the spatio-temporal change of physicochemical factors by short-term wind events, namely "island effect". Long-term survey research is needed to facilitate food-web response in marine ecosystem associated with phytoplankton biomass and physicochemical factors including the warm water current in oligotrophic offshore water of Dokdo, which may have significant role for sustainable use of Dokdo.

• Korean Journal of Environment and Ecology
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• v.33 no.5
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• pp.605-619
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• 2019

The objective of this study was to analyze eutrophication characteristics, empirical model analysis, and variation of water quality according to monsoon intensity in Hapcheon Reservoir for 16 years from 2002 to 2017. Long-term annual water quality analysis showed that Hapcheon Reservoir was in a meso-nutrition to eutrophic condition, and the eutrophic state intensified after the summer monsoon. Annual rainfall volume (high vs. low rainfall) and the seasonal intensity in each year were the key factors that regulate the long-term water quality variation provided that there is no significant change of the point- and non-point source in the watershed. Dry years and wet years showed significant differences in the concentrations of TP, TN, BOD, and conductivity, indicating that precipitation had the most direct influence on nutrients and organic matter dynamics. Nutrient indicators (TP, TN), organic pollution indicators (BOD, COD), total suspended solids, and chlorophyll-a (Chl-a), which was an estimator of primary productivity, had significant positive relations (p<0.05) with precipitation. The Chl-a concentration, which is an indicator of green algae, was highly correlated with TP, TN, and BOD, which differed from other lakes that showed the lower Chl-a concentration when nutrients increased excessively. Empirical model analysis of log-transformed TN, TP, and Chl-a indicated that the Chl-a concentration was linearly regulated by phosphorus concentration, but not by nitrogen concentration. Spatial regression analysis of the riverine, transition, and lacustrine zones of $log_{10}TN$, $log_{10}TP$, and $log_{10}CHL$ showed that TN and Chl-a had significant relations (p<0.005) while TN and Chl-a had p > 0.05, indicating that phosphorus had a key role in the algal growth. Moreover, the higher correlation of both $log_{10}TP$ and $log_{10}TN$ to $log_{10}CHL$ in the riverine zone than the lacustrine zone indicated that there was little impact of inorganic suspended solids on the light limitation in the riverine zone.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.627-646
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• 2022

Recently, the seriousness of climate change-related problems caused by global warming is growing, and the average temperature is also rising. As a result, it is affecting the environment in which various temperature-sensitive creatures and creatures live, and changes in the ecosystem are also being detected. Seasons are one of the important factors influencing the types, distribution, and growth characteristics of creatures living in the area. Among the most popular and easily recognized plant seasonal phenomena among the indicators of the climate change impact evaluation, the blooming day of flower and the peak day of autumn leaves were modeled. The types of plants used in the modeling were forsythia and cherry trees, which can be seen as representative plants of spring, and maple and ginkgo, which can be seen as representative plants of autumn. Weather data used to perform modeling were temperature, precipitation, and solar radiation observed through the ASOS Observatory of the Korea Meteorological Administration. As satellite data, MODIS NDVI was used for modeling, and it has a correlation coefficient of about -0.2 for the flowering date and 0.3 for the autumn leaves peak date. As the model used, the model was established using multiple regression models, which are linear models, and Random Forest, which are nonlinear models. In addition, the predicted values estimated by each model were expressed as isopleth maps using spatial interpolation techniques to express the trend of plant seasonal changes from 2003 to 2020. It is believed that using NDVI with high spatio-temporal resolution in the future will increase the accuracy of plant phenology modeling.

• Korean Journal of Environmental Biology
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• v.41 no.1
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• pp.18-30
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• 2023

Forest destruction is an inevitable result of the development processes. According to the environmental impact assessment, over 10% of the destroyed trees need to be recycled and transplanted to minimize the impact of forest destruction. However, the rate of successful transplantation is low, leading to a high rate of tree death. This is attributable to a lack of consideration for environmental factors when choosing a temporary site for transplantation and inadequate management. To monitor transplanted trees, a field survey is essential; however, the spatio-temporal aspect is limited. This study evaluated the applicability of remote sensing for the effective monitoring of transplanted trees. Vegetation indices based on satellite remote sensing were derived to detect time-series changes in the status of the transplanted trees at three temporary transplantation sites. The mortality rate and vitality of transplanted trees before and after the transplant have a similar tendency to the changes in the vegetation indicators. The findings of this study showed that vegetation indices increased after transplantation of trees and decreased as the death rate increased and vitality decreased over time. This study presents a method for assessing newly transplanted trees using satellite images. The approach of utilizing satellite photos and the vegetation index is expected to detect changes in trees that have been transplanted across the country and help to manage tree transplantation for the environmental impact assessment.