Potential distribution of the silver stripped skipper (Leptalina unicolor) and maiden silvergrass (Miscanthus sinensis) under climate change in South Korea

Abstract

Globally, changes in the climate and in land cover are the most prominent factors affecting the distribution of flora and fauna, including butterflies. Therefore, this study was designed to assess the impact of climate and land cover changes on the potential habitat of the endangered butterfly Leptalina unicolor and its principal host, Miscanthus sinensis, in South Korea. We developed a species distribution model using the maximum entropy modeling approach and evaluated the current and future potential distributions of both species. Currently, the potential habitat of L. unicolor is predicted to be located along the Baekdudaegan mountain range and some isolated patches of its western and southern regions, covering an area of approximately 16,865 km2. However, due to future climate change, its potential habitat would decrease on a large scale (by up to 80.39%), thus limiting its existence to the northeastern region. On the other hand, the host plant (M. sinensis) was estimated to live in all parts of the country under both current and future climate conditions, covering up to 50.45% of the country. Our results showed that future climate and land cover changes will critically reduce the habitat of L. unicolor and limit its existence to relatively cold areas. This study suggests that, in addition to the host habitat, climate and land cover changes also play important roles in the future distribution of L. unicolor. This study predicted the current and future potential habitats of L. unicolor and M. sinensis to help develop management policies for the conservation of this endangered butterfly in South Korea.

Global spatial distribution of Chromolaena odorata habitat under climate change: random forest modeling of one of the 100 worst invasive alien species

“…We ran a Spearman’s correlation test on data from the 19 bioclimatic WorldClim variables (Table S6 ) using the PROC CORR function of SAS 9.4 (SAS Institute, Inc., Cary, NC, USA), as described before 52 , 53 . We selected 6 of the 19 bioclimatic variables (Table 1 ) on the basis of their low correlation with each other (r < 0.75; Table S1 ): annual mean temperature (Bio01), mean diurnal temperature range (Bio2), isothermality (Bio03), annual precipitation (Bio12), precipitation in the wettest month (Bio13), and precipitation in the driest month (Bio14).…”

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

“…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).…”