Monitoring of the Butterfly Communities inhabited of Mt. Hallasan, Jeju island, Korea

Kim, Do‐Sung; Park, Seong‐Joon; Kim, Dong‐Soon; Cho, Young-Bok; Lee, Yeong-Don; Ahn, Nung-Ho; Kim, Ki-Gyoung; Seo, Hong-Yul; Cha, Jin-Yeol

doi:10.13047/kjee.2014.28.6.697

Cited by 6 publications

(6 citation statements)

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“…2014), has now been found at Mount Halla (Kim et al . 2014) and on Jeju Island. Moreover, as previously described, L. pandava , which was only discovered on Jeju Island in 2006 (Joo et al .…”

Section: Discussionmentioning

confidence: 98%

“…First, the spread of L. pandava has already been observed. L. pandava, which originated from western Taiwan (Fric et al 2014), has now been found at Mount Halla (Kim et al 2014) and on Jeju Island. Moreover, as previously described, L. pandava, which was only discovered on Jeju Island in 2006 (Joo et al 2008), was also discovered on Chuja Island, 65 km away from Jeju Island in 2018 (NSM & JPWNHC 2019).…”

Section: Discussionmentioning

confidence: 99%

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Prediction of climate change effects on the potential distribution of cycad blue butterfly (Luthrodes pandava) in South Korea

Shin

Kim²,

Cho

2022

Entomological Research

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Luthrodes pandava (Lepidoptera: Lycaenidae) is a major pest of the genus Cycas (Cycadales: Cycadaceae) and mainly inhabits low latitudes of Asia. Recently, L. pandava has gradually spread to other regions. L. pandava was first recorded in South Korea in 2006 and has been continuously observed on Jeju Island ever since. Adequate management and mitigation plans are necessary to prevent further spread of L. pandava throughout Korea. Therefore, this study used a species distribution model to predict the potential distribution of L. pandava under current and future climate conditions. A weighted ensemble model that incorporated the accuracy of 10 species distribution models was used to improve the forecast certainty. The potential distribution areas of L. pandava were predicted in units of 20 years from the present to 2,100 using a climate change scenario (SSP5–8.5). Under current and future climate conditions, the ensemble model predicted that L. pandava would be extensively distributed on Jeju Island and along the southern seaboard, west coast, and east coast, inhabiting 50–70% of Korea's land area by 2,100. Additionally, many sources of food for L. pandava, excluding those in the Cycas genus, have been observed in Korea. Thus, trading ports and the inland of the Korean Peninsula must be continuously monitored for outbreaks of L. pandava. The findings of this study provide essential necessary data to help mitigate the outbreak and spread of L. pandava in Korea and their associated damage to the Cycas genus.

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Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

Prediction of climate change effects on the potential distribution of cycad blue butterfly (Luthrodes pandava) in South Korea

Shin

Kim²,

Cho

2022

Entomological Research

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“…Data Set Size Accuracy FP [20] Detection mechanism based on the 2-gram method to the web page text content; the threshold adjustment method to detect defacement.…”

Section: Work Algorithmmentioning

confidence: 99%

“…Dau Hoang [22] proposed a website defacement detection method based on machinelearning techniques in his study of website defacement detection. He adopted the idea from Woonyon Kim et al [20], who argued for the n-gram method and occurrence frequency to detect the defacement in a dynamic web page and reduce the false alarms, as well as a method of threshold adjustment to reduce the false positive alarms (as the detection was for dynamic web pages). They proposed two threshold mechanisms to compare their variants in the results.…”

Section: Work Algorithmmentioning

confidence: 99%

Website Defacement Detection and Monitoring Methods: A Review

et al. 2022

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Web attacks and web defacement attacks are issues in the web security world. Recently, website defacement attacks have become the main security threats for many organizations and governments that provide web-based services. Website defacement attacks can cause huge financial and data losses that badly affect the users and website owners and can lead to political and economic problems. Several detection techniques and tools are used to detect and monitor website defacement attacks. However, some of the techniques can work on static web pages, dynamic web pages, or both, but need to focus on false alarms. Many techniques can detect web defacement. Some are based on available online tools and some on comparing and classification techniques; the evaluation criteria are based on detection accuracies with 100% standards and false alarms that cannot reach 1.5% (and never 2%); this paper presents a literature review of the previous works related to website defacement, comparing the works based on the accuracy results, the techniques used, as well as the most efficient techniques.

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“…There are two species of roe deer: the European roe deer (Capreolus capreolus), which are widely distributed over Europe, and the Siberian roe deer (Capreolus pygargus), which are distributed across northern Asia [33], including parts of Siberia, Central Asia, Northeast Asia, and Jeju Island (Figure 2). Currently, their population and habitats are decreasing due to logging and hunting; hence, roe deer have been designated as a species of Least Concern (LC) by the International Union for Conservation of Nature (IUCN) [34], and thus, warrant continuous protection.…”

Section: Target Speciesmentioning

confidence: 99%

Estimating Changes in Habitat Quality through Land-Use Predictions: Case Study of Roe Deer (Capreolus pygargus tianschanicus) in Jeju Island

Lee

2020

Sustainability

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This study predicts future land-use changes and the resulting changes in habitat quality, suggesting a method for establishing land-use management to ensure sustainable wildlife habitats. The conservation effects were verified in terms of wild animal habitat quality according to the designation of protected areas. Land-use change until 2050 was predicted using the Dyna-Conversion of Land Use Change and its effects (Dyna-CLUE) model for Jeju Island, Korea, and the change in the quality of roe deer habitats was predicted using the Integrated Valuation and Environmental Services and Tradeoffs (InVEST) model. Results indicate that, compared to 2030, urbanized area increased by 42.55 km2, farmland decreased by 81.36 km2, and natural area increased by 38.82 km2 by 2050. The average habitat quality on Jeju Island was predicted to decrease from 0.306 in 2030 to 0.303 in 2050. The average habitat quality ranged from 0.477 in 2030 to 0.476 in 2050 in protected areas and 0.281 in 2030 to 0.278 in 2050 outside protected areas. Habitat quality in protected areas was relatively high, and its reduction was limited. Areas with lower habitat quality need approaches such as expanding greenery and improving its quality. By establishing appropriate land-use plans by predicting habitat quality, wildlife habitats can be better maintained and protected, which is a primary goal of green infrastructure.

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Monitoring of the Butterfly Communities inhabited of Mt. Hallasan, Jeju island, Korea

Cited by 6 publications

References 0 publications

Prediction of climate change effects on the potential distribution of cycad blue butterfly (Luthrodes pandava) in South Korea

Prediction of climate change effects on the potential distribution of cycad blue butterfly (Luthrodes pandava) in South Korea

Website Defacement Detection and Monitoring Methods: A Review

Estimating Changes in Habitat Quality through Land-Use Predictions: Case Study of Roe Deer (Capreolus pygargus tianschanicus) in Jeju Island

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