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

Abstract

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.

Potential distribution of the critically endangered dragonfly Libellula angelina (Odonata: Libellulidae) under shared socio‐economic pathways

“…2022; Shin et al . 2022). In the case of conservation ecology, numerous articles have provided evidence for the usefulness of SDMs when planning conservation strategies for endangered species (Guisan et al .…”

“…SDMs simulate the geographic distribution based on the relevant environmental factors as well as the known occurrence records of the target species. SDMs have been widely used for conservation biology, biogeography, ecology, pest management and invasive species (Elith & Leathwick 2009;Guisan et al 2013;Gobeyn & Goethals 2019;Adhikari et al 2022;Shin et al 2022). In the case of conservation ecology, numerous articles have provided evidence for the usefulness of SDMs when planning conservation strategies for endangered species (Guisan et al 2013).…”