Anthropogenic activities and global climate change increase the risk of Chromolaena odorata invasion and habitat expansion. To predict its global distribution and habitat suitability under climate change, a random forest (RF) model was employed. The RF model, utilizing default parameters, analyzed species presence data and background information. The model revealed that the current spatial distribution of C. odorata covers 7,892,447 km². Predictions for 2061– 2080 indicate expansion of suitable habitat (42.59 and 46.30%), reduction of suitable habit (12.92 and 12.20%), and preservation of suitable habitat (87.08 and 87.80%) under the SSP (Shared Socio-economic Pathway) 2-4.5 and SSP5-8.5 scenarios, respectively, in comparison to the present distribution. Currently, C. odorata is predominantly found in South America, with limited presence in other continents. However, the data suggest that climate change will elevate the global invasion risk of C. odorata worldwide, particularly in Oceania, Africa, and Australia. Countries such as Gambia, Guinea-Bissau, and Lesotho, which currently have unsuitable habitats, are predicted to have highly suitable habitats with climate change, supporting the idea that global habitat expansion for C. odorata will occur due to climate change. This study indicates that proper management of C. odorata is crucial during the early invasion phase.

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.

Acacia mearnsii, among the 100 worst invasive weeds worldwide, negatively impacts native biodiversity, agriculture, and natural ecosystems. Global climate change, characterized by rising temperatures and altered precipitation patterns, enhances the risk of A. mearnsii invasion in Asia, making it crucial to identify high-risk areas for effective management. This study performed species distribution modeling using the maximum entropy (MaxEnt) algorithm to predict the potential introduction and spread of A. mearnsii under various climate scenarios based on shared socio-economic pathways (SSP2-4.5 and SSP5-8.5). Currently, only 4.35% of Asia is invaded, with a high invasion risk identified in six countries, including Bhutan, Lebanon, and Taiwan, where more than 75% of their areas are threatened. Under future climate scenarios, 21 countries face invasion risk, among which 14 countries, such as Georgia, Laos, Republic of Korea, and Turkey, are at moderate to very high risk, potentially encompassing up to 87.89% of their territories. Conversely, Northern Asian countries exhibit minimal changes in invasion risk and are considered relatively safe from invasion. These findings underscore that climate change will exacerbate invasion risks across Asia, emphasizing the urgent need for robust management strategies, including stringent quarantine measures and control efforts, to mitigate the threat of A. mearnsii expansion.

Oxalis latifolia, a perennial herbaceous weed, is a highly invasive species that poses a threat to agricultural lands worldwide. East Asia is under a high risk of invasion of O. latifolia under global climate change. To evaluate this risk, we employed maximum entropy modeling considering two shared socio-economic pathways (SSP2-4.5 and SSP5-8.5). Currently, a small portion (8.02%) of East Asia is within the O. latifolia distribution, with the highest coverages in Chinese Taipei, China, and Japan (95.09%, 9.8%, and 0.24%, respectively). However, our projections indicated that this invasive weed will likely be introduced to South Korea and North Korea between 2041 and 2060 and 2081 and 2100, respectively. The species is expected to cover approximately 9.79% and 23.68% (SSP2-4.5) and 11.60% and 27.41% (SSP5-8.5) of the total land surface in East Asia by these time points, respectively. South Korea and Japan will be particularly susceptible, with O. latifolia potentially invading up to 80.73% of their territory by 2081–2100. Mongolia is projected to remain unaffected. This study underscores the urgent need for effective management strategies and careful planning to prevent the introduction and limit the expansion of O. latifolia in East Asian countries.

Background: Global risk assessment of invasive weeds is a proactive strategy for identifying high-risk species and regions, predicting invasion rates and extents, and evaluating harmful impacts on native biodiversity, agriculture, and ecosystems. In this study, species distribution modeling was used to assess the global invasion risk of Ardisia elliptica, a highly invasive tropical shrub native to South and Southeast Asia that is harmful in other parts of the world, under the current climate and future climate change scenarios [shared socioeconomic pathways (SSPs) SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5] and other environmental variables, including land use and land cover change, soil moisture, soil carbon, soil pH, and human influence index. Results: Our study revealed that annual precipitation, human influence index, and precipitation in the wettest month contributed significantly to the MaxEnt model, with estimated contributions of 31.35%, 22.76%, and 14.77%, respectively. These findings suggest that the global distribution of A. elliptica is limited primarily by climatic variables, whereas anthropogenic factors also play an important role in its habitat expansion. The current invasion risk was highest in South America, Oceania (east), and Africa, affecting up to 24.51% of the total land surface area. A risk assessment of 165 countries revealed a risk of invasion in 41 countries with no records of species occurrence. Under future climate change scenarios, a significant global expansion of the distribution was predicted, with invasion in South America covering up to 48.97% of the land surface area by 2061–2080. Habitat suitability analysis revealed that 21 countries under the current climate and 47 countries under SSP5-8.5 had extremely suitable habitats for A. elliptica. Additionally, the species has already invaded at least 115 countries, while 15 countries, including Benin, Burundi, Japan, Uruguay, Swaziland, and South Korea, are predicted to shift categories from having unsuitable or poor invasion risk to having high invasion risk. Conclusions: These findings are crucial for understanding the global invasion risk of A. elliptica under substantial climate change and anthropogenic activities and support the development of effective biosecurity measures and sustainable management strategies for this harmful species at the global and national levels.

Arundo donax ranks among the world’s 100 most invasive weed species, posing significant threats to native biodiversity, agriculture, and natural ecosystems. Global climate change, characterized by increasing temperatures and increased human activities, is projected to amplify the risk of A. donax invasion worldwide. In this study, species distribution modeling via the maximum entropy algorithm was employed to predict the potential distributions of species under current and future climate scenarios on the basis of the following shared socioeconomic pathways (SSPs): SSP2-4.5 and SSP5-8.5. Our study revealed that the human influence index (HII), annual mean temperature (Bio1), and ultraviolet radiation (UV-B) were the top contributors to the model output, with contribution rates of 59%, 23.6%, and 7.3%, respectively. Currently, approximately 10.15% of the total land mass is invaded by A. donax , with 21 countries, including France, Croatia, Italy, and Spain, identified as exhibiting more than 75% of their territories at high risk of invasion. However, the future projections for 2041–2060 and 2081–2100 indicated substantial expansion in suitable habitats, covering land mass proportions of 18.40% and 24.26%, respectively, under SSP2-4.5 and 19.39% and 25.66%, respectively, under SSP5-8.5. Notably, 41 countries (SSP2-4.5) and 42 countries (SSP5-8.5) were projected to shift from low to high or very high invasion risk categories from 2081–2100. Moreover, invasion risk was projected to increase across all continents, with Africa demonstrating the most significant increase (312.08%). These findings highlight the escalating threat of A. donax under global climate change and human activities, emphasizing the urgent need for proactive management strategies, including enhanced quarantine measures and effective control programs, to limit its spread and mitigate associated risks.