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- P-ISSN2765-2203
- E-ISSN2765-2211
- KCI Candidate
Abstract
The dung beetle, Gymnopleurus mopsus (Coleoptera: Scarabaeidae), is one of endangered species in South Korea. It was last recorded in 1971. To restore this species, we introduced G. mopsus populations from eastern and southern regions of Mongolia in July 2019 and August 2019, respectively. One of the main tasks for the restoration of endangered insects is to develop breeding techniques to eventually incorporate these insects into the restoration system. In a series of laboratory experiments, we investigated effects of short-term hibernation periods on life-history traits of G. mopsus. Adult G. mopsus that had hibernated for 30, 60, and 90 days had lower survival rates than adults that had hibernated for 120 days. We also compared developmental time of these four experimental groups and found a significant difference in the egg - phase. However, the duration of hibernation did not affect the fecundity, brood-ball size, or body size of F1 adults. Follow-up studies are currently being conducted to further investigate the effect of a short-term hibernation period on population growth of G. mopsus under laboratory conditions.
Abstract
Farming practices that balance environmental friendliness with biodiversity are increasingly valuable. Wild plants on farmlands compete for nutrients with crops and create a crucial microhabitat and resources for animals such as natural enemies. Investigating farmlands and their surrounding plants with limited human and material resources has become an essential aspect of evaluating the agricultural ecosystem services. This study investigated plants in six agricultural long-term ecological research sites in Taiwan from 2017 to 2020 to determine the ideal season for investigation. Cluster analysis was performed to group habitats with similar plant composition, and the species–area curves of the clusters in each season were created. The results indicated that the agricultural ecosystem could be divided into farmlands, banks, orchards, and tea gardens. The habitats were divided into farmland, bank, Chia-Yi orchard, Gu-Keng orchard, and tea garden clusters. Ground plant cover can be investigated all year with at least 18 quadrats. However, if human and material resources are limited, 10 quadrats should be the minimum for farmlands in autumn and for the other microhabitats in spring. The minimum number of quadrats is 10 for banks, 17 for orchards, and 9 for tea gardens.
Abstract
Species distribution models are a useful tool for predicting future distribution and establishing a preemptive response of invasive species. However, few studies considered the possibility of habitat for the aquatic organism and the number of target sites was relatively small compared to the area. Environmental DNA (eDNA) is the emerging tool as the methodology obtaining the bulk of species presence data with high detectability. Thus, this study applied eDNA survey results of Micropterus salmoides and Lepomis macrochirus to species distribution modeling by seasons in the Anyang stream network. Maximum Entropy (MaxEnt) model evaluated that both species extended potential distribution area in October compared to July from 89.1% (12,110,675 m2) to 99.3% (13,625,525 m2) for M. salmoides and 76.6% (10,407,350 m2) to 100% (13,724,225 m2) for L. macrochirus. The prediction value by streams was varied according to species and seasons. Also, models elucidate the significant environmental variables which affect the distribution by seasons and species. Our results identified the potential of eDNA methodology as a way to retrieve species data effectively and use data for building a model.
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
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
Ecological research relies on the interpretation of large amounts of visual data obtained from extensive wildlife surveys, but such large-scale image interpretation is costly and time-consuming. Using an artificial intelligence (AI) machine learning model, especially convolution neural networks (CNN), it is possible to streamline these manual tasks on image information and to protect wildlife and record and predict behavior. Ecological research using deep- learning-based object recognition technology includes various research purposes such as identifying, detecting, and identifying species of wild animals, and identification of the location of poachers in real-time. These advances in the application of AI technology can enable efficient management of endangered wildlife, animal detection in various environments, and real-time analysis of image information collected by unmanned aerial vehicles. Furthermore, the need for school education and social use on biodiversity and environmental issues using AI is raised. School education and citizen science related to ecological activities using AI technology can enhance environmental awareness, and strengthen more knowledge and problem-solving skills in science and research processes. Under these prospects, in this paper, we compare the results of our early 2013 study, which automatically identified African cichlid fish species using photographic data of them, with the results of reanalysis by CNN deep learning method. By using PyTorch and PyTorch Lightning frameworks, we achieve an accuracy of 82.54% and an F1-score of 0.77 with minimal programming and data preprocessing effort. This is a significant improvement over the previous our machine learning methods, which required heavy feature engineering costs and had 78% accuracy.
Abstract
Polyphylla laticollis manchurica Semenov, 1900, is a critically endangered species in the Republic of Korea and is strictly protected as a Class I endangered species. Although this beetle species faces a threat of extinction, its ecological understanding is limited. Previous studies conducted on this species in the Republic of Korea have focused only on its taxonomy and mitochondrial genome sequences. Herein, we report an observation of the mating of adults of P. l. manchurica in June 2021, during an ongoing study on Korean beetles. This incidence was reported around light sources from newly constructed townhouses near Geumgang River. Larval habitats were observed along the river between April 2022 and March 2023. Particularly, two larvae were found inside the plant debris, and three were found under the roots of reeds. This study provides key information on the mating ecology of P. l. manchurica that can assist conservation efforts of this critically endangered species.
Abstract
The Kentish Plover (Charadrius alexandrinus; family Charadriidae; genus Charadrius) is a small bird that moves from continent to continent depending on the season. On the Kentish Plovers, phylogenetic studies have been widely conducted to classify different species or subspecies and to determine the time of speciation. However, the perspectives on the interspecific or intraspecific relationships in the phylogenetic analysis of Kentish Plovers remain debatable. Here, we reviewed the differences between the Kentish and Snowy Plovers (C. nivosus) in terms of their morphology, ecology, and genetic information. Particularly, their differences in genetic information can be well demonstrated; however, the intraspecies differences in the populations that live in different environments can relatively be poorly explained. We suggest that not only genetic features but also morphological, ecological, and behavioral traits are important when comparing the Kentish Plovers with other species, such as the Snowy Plovers, in phylogenetic studies. Furthermore, we suggest that phylogenetic studies on the subspecies of the Kentish and Snowy Plovers should be conducted for their better identification.
Abstract
The rapid development of technologies in unmanned aerial vehicles (UAVs) has led to their use in various areas. UAVs are mainly used for commercial purposes, but their utilization is increasingly important in other areas because their operation cost is less than satellites and aerial imaging. The utilization of UAVs in the environment/ecology area is relatively new. Therefore, identifying the trends of UAV-related spatial information is significant in basic research for UAV utilization. This study quantitatively identified domestic and international research trends related to UAV utilization and analyzed research areas. An attempt was also made to identify upcoming UAV-related topics in the environment/ecology research field using text mining to analyze the bibliographic information of global research literature. Domestic UAV-related studies were classified into seven clusters where basic research on “UAV technology/industry trends” was abundant, and studies on data collection and analysis through UAV remote sensing technology have increased since 2015. Eight clusters were identified for international studies where the most active research area international was “remote sensing technology/data analysis”. In addition, Canopy, Classification, Forest, Leaf Area Index, Normalized Difference Vegetation Index, Temperature, Tree, and Atmosphere appeared as the main keywords related to environment and ecology. The appearance frequencies and association strengths were high because the advancement in UAV optical sensor technology and the rapid development of image processing technology enabled the acquisition of data that could not be obtained from existing spatial information. They are recognized as future research topics as related domestic studies have begun corresponding to international research.
Abstract
Korean fir (Abies koreana) is an evergreen coniferous tree species that is unique to South Korea. A. koreana is found in a limited sub-alpine habitat and is considered particularly vulnerable to climate change. Identification of populations vulnerable to climate change is an important component of conservation programs. In this study, a heat stress-induced transcriptome RNA-seq dataset was used to identify a subset of six genes for assessment as candidate marker genes for ecologically vulnerable populations. Samples of A. koreana were isolated from ecologically stable and vulnerable regions of the Halla and Jiri mountains, and the expression levels of the six candidate markers were assessed using quantitative real-time polymerase chain reaction. All six of the candidate genes exhibited higher expression levels in samples from vulnerable regions compared with stable regions. These results confirm that the six high temperature-induced genes can be used as diagnostic markers for the identification of populations of A. koreana that are experiencing stress due to the effects of climate change.
