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- P-ISSN2765-2203
- E-ISSN2765-2211
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Abstract
This study surveyed the changes in the proportion of Ecological and Natural Map (ENM) grades in Korea, the distribution ratio of ENM 1st-grade areas by region, and the current status of regional public appeals for the five-year period from 2017 to 2021. The nationwide changes in ENM grades revealed an increase in 1st-grade, 3rd-grade, and separately managed areas but a decrease in the ratio of 2nd-grade areas. Nationwide, Gangwon had the highest distribution ratio of 1st-grade areas, at 46.77%, while Gwangju had the lowest, at 0.05%. In the five-year study period, 383 appeals concerning ENM grades were received and processed. Gangwon had the greatest number of appeals, with 96, while Sejong had the fewest, with 1. A significant correlation was observed between the distribution ratio of 1st-grade areas and public appeals.
Abstract
The conservation of the raccoon dog (Nyctereutes procyonoides) in South Korea requires the protection and preservation of natural habitats while additionally ensuring coexistence with human activities. Applying habitat map modeling techniques provides information regarding the distributional patterns of raccoon dogs and assists in the development of future conservation strategies. The purpose of this study is to generate potential habitat distribution maps for the raccoon dog in South Korea using geospatial technology-based models. These models include the frequency ratio (FR) as a bivariate statistical approach, the group method of data handling (GMDH) as a machine learning algorithm, and convolutional neural network (CNN) and long short-term memory (LSTM) as deep learning algorithms. Moreover, the imperialist competitive algorithm (ICA) is used to fine-tune the hyperparameters of the machine learning and deep learning models. Moreover, there are 14 habitat characteristics used for developing the models: elevation, slope, valley depth, topographic wetness index, terrain roughness index, slope height, surface area, slope length and steepness factor (LS factor), normalized difference vegetation index, normalized difference water index, distance to drainage, distance to roads, drainage density, and morphometric features. The accuracy of prediction is evaluated using the area under the receiver operating characteristic curve. The results indicate comparable performances of all models. However, the CNN demonstrates superior capacity for prediction, achieving accuracies of 76.3% and 75.7% for the training and validation processes, respectively. The maps of potential habitat distribution are generated for five different levels of potentiality: very low, low, moderate, high, and very high.
Abstract
Sanankerto is one of pilot projects for tourism villages in Indonesia due to its natural tourism potential with a 24-ha bamboo forest located in Boon Pring Andeman area. However, the distribution of existing bamboo has never been identified or mapped. Thus, the management is facing difficulty in planning and developing tourism potential as well as spatial management in the area. Therefore, the objectives of this study were to identify and analyze the structure of bamboo vegetation in the Boon Pring Tourism village and to perform vegetation mapping. The type of research was descriptive exploratory with a cluster sampling technique (i.e., a two-stage cluster) covering an area of ± 10 ha. Bamboo vegetation analysis was performed by calculating diversity index (H’), evenness index (E), and Species Richness index (R). Data were collected through observation and interviews with local people and the manager to determine zonation division. Mapping of bamboo vegetation based on zoning was processed into thematic maps using ArcGis 10.3. Micro climatic factors were measured with three replications for each sub-cluster. Data were analyzed descriptively and quantitatively. Nine species of bamboo identified. Diversity, evenness, and species richness indices differed at each location. Activities of local communities, tourists, and manager determined the presence, number, and distribution of bamboo species. These bamboo distribution maps in three zoning (utilization, buffer, and core) can be used by manager for planning and developing natural tourism potential.
Abstract
Most of the islands of Korea are distributed in the South and West Sea, and it consists of independent small stream. As a result, the fish community that inhabits the island's stream is isolated from the mainland and other island. This study utilized a Self-Organizing Map (SOM) and a random forest model to analyze the relationship between environmental variables and fish communities inhabiting islands in South Korea. Through the SOM analysis, the fish communities were divided into three clusters, and there were differences in biotic and abiotic factors between these groups. Cluster I consisted of sites with relatively larger island areas and a higher number of species and population. It was found that 15 out of 16 indicator species were included. Meanwhile, the remaining clusters had fewer species and populations. Cluster II, especially, showed the lowest impact from physical variables such as water width and depth. As a result of predicting the species richness using the random forest model, physical variables in habitats, such as stream width and water depth, had a relatively higher importance on species richness. On the other hand, forest area was the most important variables for predicting Shannon diversity, followed by maximum water depth, and gravel. The results suggest that this study can be used as basic data for establishing a stream ecosystem management strategy in terms of conservation and protection of biological resources in streams of islands.
Abstract
The study has been carried out with an objective to prepare Siberian roe deer habitat potential maps in South Korea based on three geographic information system-based models including frequency ratio (FR) as a bivariate statistical approach as well as convolutional neural network (CNN) and long short-term memory (LSTM) as machine learning algorithms. According to field observations, 741 locations were reported as roe deer’s habitat preferences. The dataset were divided with a proportion of 70:30 for constructing models and validation purposes. Through FR model, a total of 10 influential factors were opted for the modelling process, namely altitude, valley depth, slope height, topographic position index (TPI), topographic wetness index (TWI), normalized difference water index, drainage density, road density, radar intensity, and morphological feature. The results of variable importance analysis determined that TPI, TWI, altitude and valley depth have higher impact on predicting. Furthermore, the area under the receiver operating characteristic (ROC) curve was applied to assess the prediction accuracies of three models. The results showed that all the models almost have similar performances, but LSTM model had relatively higher prediction ability in comparison to FR and CNN models with the accuracy of 76% and 73% during the training and validation process. The obtained map of LSTM model was categorized into five classes of potentiality including very low, low, moderate, high and very high with proportions of 19.70%, 19.81%, 19.31%, 19.86%, and 21.31%, respectively. The resultant potential maps may be valuable to monitor and preserve the Siberian roe deer habitats.
Abstract
This study analyzed research trends in the field of ecological research. Data were collected based on a keyword search of the SCI, SSCI, and A&HCI databases from January 2002 to September 2022. The seven keywords, including biodiversity, ecology, ecotourism, species, climate change, ecosystem, restoration, wildlife, were recommended by ecological research experts. Word clouds were created for each of the searched keywords, and topic map analysis was performed. Topic map analysis using biodiversity, climate change, ecology, ecosystem, and restoration each generated 10 topics; topic maps analysis using the ecotourism keyword generated 5 topics; and topic map analysis using the wildlife keyword generated 4 topics. Each topic contained six keywords.
Abstract
We analyzed data of endangered mammals in the 1st grade zone of the Ecological and Natural Map of Korea that were obtained through 202 field surveys over six years. Five endangered mammal species were identified including otters, long-tailed gorals, martens, leopard cats, and flying squirrels. The total number of habitat traces collected was 918, of which 897 traces (97.7%) were excrement types. The total surveyed distance was 697.7 km and there were 2,184 grids of 250×250 m each. Of these grids, 441 or 20.2% were confirmed as habitats of endangered mammals. Moreover, we analyzed results of repeated surveys in the same area by converting them into individual one-time surveys, accounting for 23.1% of the total area. The flying squirrel showed a low correlation with the frequency of field surveys but showed many habitats in a specific season. Leopard cats and martens were correlated with the frequency of field surveys. Results of analysis confirm that the grid method used for establishing the Ecological and Natural Map is unsuitable for the habitat division of flying squirrels, otters, leopard cats, and martens, and it does not reflect the actual habitats of these four species. Therefore, we propose that the concept of the habitat grid of species must be reevaluated and improved, specifically for endangered mammals.
Abstract
During our observations of changes in halophyte distribution in Hampyeong Bay over a period of five years, we found that the distribution area showed a maintenance for Phragmites communis community, a tendency of gradual increase for Zoysia sinica community, gradual decrease for Suaeda maritima community, and disappearance for Limonium tetragonum community during the studied period. The Phragmites communis community stably settled in areas adjacent to land and appeared not to be significantly affected by physical factors (such as tides and waves) or disturbances caused by biological factors (such as interspecific competition). Among studied species, germination time was shown to be the fastest for Suaeda maritima. In addition, this species showed certain characteristics that allowed it to settle primarily in new habitats formed by sand deposition as its growth was not halted under conditions with high amounts of sand and high organic matter content. However, in areas where Zoysia sinica and Suaeda maritima resided together, the area inhabited by Suaeda maritima gradually decreased due to interspecific competition between the two species. This was believed to be the result of a sharp decrease in the germination of Suaeda maritima since May, while the germination of Zoysia sinica was continuously maintained, indicating that the latter had an advantage in terms of seedling competition. In the case of the Limonium tetragonum community, its habitat was found to have been completely destroyed because it was covered by sand. The study area was confirmed to have undergone a large change in topography as tides and waves resulted in sand deposition onto these lands. Hampyeong Bay is considered to have experienced changes in halophyte distribution related to certain complex factors, such as changes in physical habitats and changes in biological factors such as interspecific competition.
Abstract
In order to support biomimicry technology development, it is necessary to develop an omnidirectional service platform which can recommend principles of biomimicry and business ideas, providing experts’ networks and carrying out their relevant education and promotion on the ground of baseline data and application research materials related to biomimicry. This study was conducted to establish any probable plans for construction and utilization of the future open-platform which will collect and serve the technology of biomimicry. Accordingly, biological and ecological information databases were examined along with the appreciation of construction and management of major biomimicry DB, and, based on the materials from the interview of related experts, a customer journey map was schematized. Lastly, in order to suggest a mid-to-long-term target-model, the roles of a future biomimicry knowledge service-platform were determined along with the potential plans for its construction and management based on case analysis and customers’ needs.
Abstract
Predictions of suitable habitat areas can provide important information pertaining to the risk assessment and management of alien plants at early stage of their establishment. Here, we predict the invasion potential of Muhlenbergia capillaris (pink muhly) in South Korea using five bioclimatic variables. We adopt four models (generalized linear model, generalized additive model, random forest (RF), and artificial neural network) for projection based on 630 presence and 600 pseudo-absence data points. The RF model yielded the highest performance. The presence probability of M. capillaris was highest within an annual temperature range of 12 to 24°C and with precipitation from 800 to 1,300 mm. The occurrence of M. capillaris was positively associated with the precipitation of the driest quarter. The projection map showed that suitable areas for M. capillaris are mainly concentrated in the southern coastal regions of South Korea, where temperatures and precipitation are higher than in other regions, especially in the winter season. We can conclude that M. capillaris is not considered to be invasive based on a habitat suitability map. However, there is a possibility that rising temperatures and increasing precipitation levels in winter can accelerate the expansion of this plant on the Korean Peninsula.
