Background: Invasive plant species are considered a major threat to biodiversity, ecosystem functioning, and human wellbeing worldwide. Climatically suitable ranges for invasive plant species are expected to expand due to future climate change. The identification of current invasions and potential range expansion of invasive plant species is required to plan for the management of these species. Here, we predicted climatically suitable habitats for 11 invasive plant species and calculated the potential species richness and their range expansions in different provinces of the Republic of Korea (ROK) under current and future climate change scenarios (RCP 4.5 and RCP 8.5) using the maximum entropy (MaxEnt) modeling approach. Results: Based on the model predictions, areas of climatically suitable habitats for 90.9% of the invasive plant species are expected to retain current ecological niches and expand to include additional climatically suitable areas under future climate change scenarios. Species richness is predicted to be relatively high in the provinces of the western and southern regions (e.g., Jeollanam, Jeollabuk, and Chungcheongnam) under current climatic conditions. However, under future climates, richness in the provinces of the northern, eastern, and southeastern regions (e.g., Seoul, Incheon, Gyeonggi, Gyeongsangnam, Degue, Busan, and Ulsan) is estimated to increase up to 292%, 390.75%, and 468.06% by 2030, 2050, and 2080, respectively, compared with the current richness. Conclusions: Our study revealed that the rates of introduction and dispersion of invasive plant species from the western and southern coasts are relatively high and are expanding across the ROK through different modes of dispersion. The negative impacts on biodiversity, ecosystem dynamics, and economy caused by invasive plant species will be high if preventive and eradication measures are not employed immediately. Thus, this study will be helpful to policymakers for the management of invasive plant species and the conservation of biodiversity.

Predicting the distribution of invasive weeds under climate change is important for the early identification of areas that are susceptible to invasion and for the adoption of the best preventive measures. Here, we predicted the habitat suitability of 16 invasive weeds in response to climate change and land cover changes in South Korea using a maximum entropy modeling approach. Based on the predictions of the model, climate change is likely to increase habitat suitability. Currently, the area of moderately suitable and highly suitable habitats is estimated to be 8877.46 km², and 990.29 km², respectively, and these areas are expected to increase up to 496.52% by 2050 and 1439.65% by 2070 under the representative concentration pathways 4.5 scenario across the country. Although habitat suitability was estimated to be highest in the southern regions (<36° latitude), the central and northern regions are also predicted to have substantial increases in suitable habitat areas. Our study revealed that climate change would exacerbate the threat of northward weed invasions by shifting the climatic barriers of invasive weeds from the southern region. Thus, it is essential to initiate control and management strategies in the southern region to prevent further invasions into new areas.

Subalpine ecosystems at high altitudes and latitudes are particularly sensitive to climate change. In South Korea, the prediction of the species richness of subalpine plant species under future climate change is not well studied. Thus, this study aims to assess the potential impact of climate change on species richness of subalpine plant species (14 species) in the 17 mountain national parks (MNPs) of South Korea under climate change scenarios’ representative concentration pathways (RCP) 4.5 and RCP 8.5 using maximum entropy (MaxEnt) and Migclim for the years 2050 and 2070. Altogether, 723 species occurrence points of 14 species and six selected variables were used in modeling. The models developed for all species showed excellent performance (AUC > 0.89 and TSS > 0.70). The results predicted a significant loss of species richness in all MNPs. Under RCP 4.5, the range of reduction was predicted to be 15.38–94.02% by 2050 and 21.42–96.64% by 2070. Similarly, under RCP 8.5, it will decline 15.38–97.9% by 2050 and 23.07–100% by 2070. The reduction was relatively high in the MNPs located in the central regions (Songnisan and Gyeryongsan), eastern region (Juwangsan), and southern regions (Mudeungsan, Wolchulsan, Hallasan, and Jirisan) compared to the northern and northeastern regions (Odaesan, Seoraksan, Chiaksan, and Taebaeksan). This result indicates that the MNPs at low altitudes and latitudes have a large effect on the climate change in subalpine plant species. This study suggested that subalpine species are highly threatened due to climate change and that immediate actions are required to conserve subalpine species and to minimize the effect of climate change.

Species distribution modeling is widely used for evaluating invasion risk, and for prioritizing areas for the control and management of invasive species. However, selecting a modeling tool that accurately predicts species invasion risk requires a systematic approach. In this study, five species distribution models (SDMs), namely, artificial neural network (ANN), generalized linear model (GLM), multivariate adaptive regression splines (MARS), maximum entropy (MaxEnt), and random forest (RF), were performed and evaluated their model performance using the mean value of area under the curve (AUC), true skill statistics (TSS), and Kappa scores of 12 ecosystem disturbing alien plant species (EDAPS). The mean evaluation metric scores were highest in RF (AUC = 0.924 ± 0.058, TSS = 0.789 ± 0.109, Kappa = 0.671 ± 0.096, n = 12) and lowest in ANN. The ANOVA of AUC, TSS, and Kappa metrics revealed the RF model was significantly different from other SDMs and was therefore selected as the relatively best model. The potential distribution area and invasion risk for each EDAPS were quantified. Under the current climate conditions of South Korea, the average potential distribution area of EDAPS was estimated to be 13,062 km². However, in future climate change scenarios, the average percentage change of EDAPS distribution relative to the current climate was predicted to be increased over 219.93%. Furthermore, under the current climate, 0.16% of the area of the country was estimated to be under a very high risk of invasion, but this would increase to 60.43% by 2070. Invasion risk under the current climate conditions was highest in the northwestern, southern, and southeastern regions, and in densely populated cities, such as Seoul, Busan, and Daegu. By 2070, invasion risk was predicted to expand across the whole country except in the northeastern region. These results suggested that climate change induced the risk of EDAPS invasiveness, and SDMs could be valuable tools for alien and invasive plant species risk assessment.

The global climate change, including increases in temperature and precipitation, may exacerbate the invasion by P. hysterophorus. Here, MaxEnt modeling was performed to predict P. hysterophorus distribution worldwide and in South Korea under the current and future climate global climate changes, including increases in temperature and precipitation. Under the current climate, P. hysterophorus was estimated to occupy 91.26%, 83.26%, and 62.75% of the total land area of Australia, South America, and Oceania, respectively. However, under future climate scenarios, the habitat distribution of P. hysterophorus would show the greatest change in Europe (56.65%) and would extend up to 65°N by 2081–2100 in South Korea, P. hysterophorus currently potentially colonizing 2.24% of the land area, particularly in six administrative divisions. In the future, P. hysterophorus would spread rapidly, colonizing all administrative divisions, except Incheon, by 2081–2100. Additionally, the southern and central regions of South Korea showed greater habitat suitability than the northern region. These findings suggest that future climate change will increase P. hysterophorus distribution both globally and locally. Therefore, effective control and management strategies should be employed around the world and in South Korea to restrict the habitat expansion of P. hysterophorus.