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- P-ISSN2765-2203
- E-ISSN2765-2211
- KCI Candidate
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
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
The Tibetan Plateau is home to the only alpine crane species, the black-necked crane (Grus nigricollis). Conservation efforts are severely hampered by a lack of knowledge on the spatial distribution and breeding habitats of this species. The ecological niche modeling framework used to predict the spatial distribution of this species, based on the maximum entropy and occurrence record data, allowed us to generate a species-specific spatial distribution map in Ladakh, Trans-Himalaya, India. The model was created by assimilating species occurrence data from 486 geographical sites with 24 topographic and bioclimatic variables. Fourteen variables helped forecast the distribution of black-necked cranes by 96.2%. The area under the curve score for the model training data was high (0.98), indicating the accuracy and predictive performance of the model. Of the total study area, the areas with high and moderate habitat suitability for black-necked cranes were anticipated to be 8,156 km2 and 6,759 km2, respectively. The area with high habitat suitability within the protected areas was 5,335 km2. The spatial distribution predicted using our model showed that the majority of speculated conservation areas bordered the existing protected areas of the Changthang Wildlife Sanctuary. Hence, we believe, that by increasing the current study area, we can account for these gaps in conservation areas, more effectively.
Abstract
This study aimed to identify the initial migratory macroinvertebrate species in two newly created mountain wetlands. To analyze the initial immigration species of macroinvertebrates, two experimental sites and two control sites were selected after habitat creation and investigated thrice from spring to fall. Benthic macroinvertebrates were collected quantitatively from each site using a Surber sampler and Modified D-frame deep net. After restoration at the two experimental sites, the number of macroinvertebrate species and individuals gradually increased from spring to fall and continued to increase over time with the development of waterside vegetation and habitat stabilization at the experimental sites. The species initially introduced to mountain wetlands after their creation were Ephemera strigata, Ephemera orientalis, Chironomidae sp., and Aquaris paludum. Subsequently, predators such as Davidius lunatus, Sieboldius albardae, Oyamia nigribasis, and Sialis longidens were introduced. Additionally, as a differentiating physicochemical factor between the two habitats, current velocity, which determines the distribution characteristics of benthic macroinvertebrates, and water temperature, which impacts the growth of organisms, showed a relatively stronger influence.
Abstract
Understanding the carrying capacity of a habitat is crucial for effectively managing populations of wild boars (Sus scrofa), which are designated as harmful wild animal species in national parks. Carrying capacity refers to the maximum population size supported by a park's environmental conditions. This study aimed to estimate the appropriate wild boar population size by integrating population characteristics and habitat suitability for wild boars in the Bukhansan National Park using the HexSim program. Population characteristics included age, survival, reproduction, and movement. Habitat suitability, which reflects prospecting and resource acquisition, was determined using the Maximum Entropy model. This study found that the optimal population size for wild boar ranged from 217 to 254 individuals. The population size varied depending on the amount of resources available within the home range, indicating fewer individuals in a larger home range. The estimated wild boar population size was 217 individuals for the minimum amount of resources (50% minimum convex polygon [MCP] home range), 225 individuals for the average amount of resources (95% MCP home range), and 254 individuals for the maximum amount of resources (100% MCP home range). The results of one-way analysis of variance revealed a significant difference in wild boar population size based on the amount of resources within the home range. These findings provide a basis for the development and implementation of effective management strategies for wild boar populations.
