U.S.-Korea economic relations

노트 : A publication of the Korea Economic Institute and the Korea Institute for International Economic Polic

Introduction and Spread of the Invasive Alien Species Ageratina altissima in a Disturbed Forest Ecosystem

Invasive alien species (IAS) not only displace nearby indigenous plants and lead to habitat simplification but also cause severe economic damage by invading arable lands. IAS invasion processes involve external forces such as species characteristics, IAS assemblage traits, environmental conditions, and inter-species interactions. In this study, we analyzed the invasion processes associated with the introduction and spread of Ageratina altissima, a representative invasive plant species in South Korea. We investigated 197 vegetation quadrats (2 × 20 m) in regions bordering 47 forests in southern Seoul and Gyeonggi-do, South Korea. A total of 23 environmental variables were considered, which encompassed vegetation, topography, land use, and landscape ecology indices. The model was divided into an edge and an interior model and analyzed using logistic regression and a decision tree (DT) model. The occurrence of Ageratina altissima was confirmed in 61 sites out of a total of 197. According to our analysis, Ageratina altissima easily invaded forest edges with low density. The likelihood of its occurrence increased with lower elevation and gentler slope. In contrast, the spread of Ageratina altissima in the forest interior, especially based on seed spread and permeability, was favored by a lower elevation and gentler slopes. The analysis of Ageratina altissima settlement processes in forest edges coupled with the DT model demonstrated that land characteristics, such as the proximity to urbanized areas and the number of shrub and tree species, play a pivotal role in IAS settlement. In the forest interior, Ageratina altissima did not occur in 68 of the 71 sites where the soil drainage was under 2.5%, and it was confirmed that the tree canopy area had a significant impact on forest spread. Based on these results, it can be assumed that Ageratina altissima has spread in South Korean forests in much the same way as other naturalized species. Therefore, vegetation management strategies for naturalized species should be developed in parallel with land use management policy in regions surrounding forest edges to successfully manage and control Ageratina altissima invasion

A Study on Wetland Cover Map Formulation and Evaluation Using Unmanned Aerial Vehicle High-Resolution Images

Wetlands possess significant ecological value and play a crucial role in the environment. Recent advancements in remote exploration technology have enabled a quantitative analysis of wetlands through surveys on the type of cover present. However, the classification of complex cover types as land cover types in wetlands remains challenging, leading to ongoing studies aimed at addressing this issue. With the advent of high-resolution sensors in unmanned aerial vehicles (UAVs), researchers can now obtain detailed data and utilize them for their investigations. In this paper, we sought to establish an effective method for classifying centimeter-scale images using multispectral and hyperspectral techniques. Since there are numerous classes of land cover types, it is important to build and extract effective training data for each type. In addition, computer vision-based methods, especially those that combine deep learning and machine learning, are attracting considerable attention as high-accuracy methods. Collecting training data before classifying by cover type is an important factor that which requires effective data sampling. To obtain accurate detection results, a few data sampling techniques must be tested. In this study, we employed two data sampling methods (endmember and pixel sampling) to acquire data, after which their accuracy and detection outcomes were compared through classification using spectral angle mapper (SAM), support vector machine (SVM), and artificial neural network (ANN) approaches. Our findings confirmed the effectiveness of the pixel-based sampling method, demonstrating a notable difference of 38.62% compared to the endmember sampling method. Moreover, among the classification methods employed, the SAM technique exhibited the highest effectiveness, with approximately 10% disparity observed in multispectral data and 7.15% in hyperspectral data compared to the other models. Our findings provide insights into the accuracy and classification outcomes of different models based on the sampling method employed in spectral imagery

Prediction of Native Seed Habitat Distribution According to SSP Scenario and Seed Transfer Zones: A Focus on <i>Acer pictum</i> subsp. <i>mono</i> and <i>Quercus acuta</i>

Acer pictum and Quercus acuta are native species recommended for restoration. To restore ecosystem functions and maintain natural ecosystems, it is suggested to deploy well-adapted and locally adapted plant material, and this notion is gaining interest. Studying how species change in response to climate change is an important part of forest restoration planning. Our method uses climate data to define the habitat range of species and to identify regions with relatively similar climates through Seed Transfer Zones (STZs). Potential habitat suitability changes of A. pictum and Q. acuta were identified under various environmental scenarios using seven climatic factors and five topographical factors. The MaxEnt algorithm was used to predict potential habitat suitability in current and future (1980–2100) climate change scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5). STZs are maps of areas with comparable climates and have been used to determine the climates of potentially habitable areas. This helps to minimize the maladaptation of seed movement within the same area. As a result, A. pictum growth increased along the southern coastal area and drainage was the paramount factor influencing A. pictum distribution. By checking the climate of regions with high habitability in STZs (Winter Minimum Temperature (WMT) 15–20 °F, Annual Heat: Moisture (AHM) 16–19 °C/m zone, WMT 20–25 °F, AHM 16–19 °C/m located in the zone), Q. acuta was shown to move northward with climate change centering on the southern coastal area. Additionally, Annual Precipitation (Bio12) was the most significant factor influencing Q. acuta distribution. In confirming the climate of areas with high habitability in STZs, we verified that habitat density was high in the WMT 10–15 °F, AHM 19–21 °C/m zone and WMT 20–25 °F, AHM 19–21 °C/m zone. This study establishes that the potential distributions of A. pictum and Q. acuta are affected by climate change. It supplies evidence for ecological restoration and sustainable development, and can formulate future conservation and management plans for economically valuable species