Predictions of suitable habitat areas within a specific region can provide important information to assist in the management of invasive plants. Here, we predict the current and future potential distribution of Solidago altissima (tall goldenrod) in South Korea using climatic and topographic variables and anthropogenic activities. We adopt four single models (the generalized linear model, generalized additive model, random forest, and an artificial neural network) and a weighted ensemble model for the projection based on 515 field survey points. The results showed that suitable areas for S. altissima were mainly concentrated in the southwest regions of South Korea, where temperatures are higher than in other regions, especially in the winter season. Solar radiation and Topographic Wetness Index (TWI) were also positively associated with the occurrence of S. altissima. Anthropogenic effects and distances from rivers were found to be relatively less important variables. Based on six selected explanatory variables, suitable habitat areas for S. altissima have expanded remarkably with climate changes. This range expansion is likely to be stronger northward in west coastal areas. For the SSP585 scenario, our model predicted that suitable habitat areas increased from 16,255 km² (16.2% of South Korea) to 44,551 km² (44.4%) approximately over the past thirty years. Our results show that S. altissima is highly likely to expand into non-forest areas such as roadsides, waterfront areas, and abandoned urban areas. We propose that, based on our projection maps, S. altissima should be removed from its current margin areas first rather than from old central population areas.

A regional decline in the Korean fir (Abies koreana) has been observed since the 1980s in the subalpine region. To explain this decline, it is important to investigate the degree to which environmental factors have contributed to plant distributions on diverse spatial scales. We applied a hierarchical regression model to determine quantitatively the relationship between the abundance of Korean fir (seedlings) and diverse environmental factors across two different ecological scales. We measured Korean fir density and the occurrence of its seedlings in 102 (84) plots nested at five sites and collected a range of environmental factors at the same plots. Our model included hierarchical explanatory variables at both site-level (weather conditions) and plot-level (micro-topographic factors, soil properties, and competing species). The occurrence of Korean fir seedlings was positively associated with moss cover and rock cover but negatively related to dwarf bamboo cover. At the site level, winter precipitation was significantly and positively related to the occurrence of seedlings. A hierarchical Poisson regression model revealed that Korean fir density was negatively associated with slope aspect, topographic position index, Quercus mongolica cover, and mean summer temperature. Our results suggest that rising temperature, drought, and competition with other species are factors that impede the survival of the Korean fir. We can predict that the population of Korean fir will continue to decline in the subalpine, and only a few Korean fir will survive on northern slopes or valleys due to climate change.

Invasive alien plants can severely threaten biodiversity and cause economic losses in the agricultural industry; therefore, identifying the critical environmental factors related to the distribution of alien plants plays a crucial role in ecosystem management. In this study, we applied partial least squares regression (PLSR) and geographically weighted regression (GWR) to estimate the important environmental factors affecting the spread of two invasive and expansive plants, Lactuca scariola L. and Aster pilosus Willd., across South Korea. GWR provides more accurate predictions than ordinary least squares regression, and the local coefficients of GWR allow for the determination of the spatial relationships between alien plant distributions and environmental variables. Based on the model’s results, the distributions of these alien species were significantly associated with anthropogenic effects, such as human population density, residential area, and road density. Furthermore, the two alien species can establish themselves in habitats where native plants cannot thrive, owing to their broad tolerance to temperature and drought conditions. This study suggests that urban development and expansion can facilitate the invasion of these species in metropolitan cities.

Phenological events are key indicators for the assessment of climate change impacts on ecosystems. Most previous studies have focused on identifying the timing of phenological events, such as flowering, leaf-out, leaf-fall, etc. In this study, we explored the characteristics of the green chromatic coordinate (GCC) values of the evergreen broadleaf tree (Quercus acuta Thunb.), which is a widely used index that serves as a proxy for the seasonal and physiological responses of trees. Additionally, we estimated their relationship with meteorological variables using time series models, including time series decomposition and a seasonal autoregressive integrated moving average with exogenous regressors (SARIMAX). Our results showed that the GCC values and the meteorological variables, which were collected at daily intervals, exhibited a strong autocorrelation and seasonality. This suggests that time series analysis methods are more suitable than ordinary least squares (OLS) regression methods for the fulfillment of statistical assumptions. The time series analysis results highlighted a strong association between precipitation and GCC variation in evergreen broadleaf trees, particularly during the dry season. These results improve our understanding of the response of plant phenology to climate change.

Although rainfall is a major determinant of soil moisture content (SMC), various factors affect SMC. The effects of these environmental factors contribute to spatial heterogeneity in SMC, which influences diverse ecological processes. To better understand the dynamics in SMC, litter and slope gradient should be considered. To this end, we analyzed the impacts of litter and slope gradient on SMC from 2020 to 2021 on Mt. Jeombong, located in a temperate deciduous broadleaf forest. We classified the study period into foliage (with a developed canopy) and non-foliage (after leaf fall) seasons. Our results indicated that SMC was affected by slope gradient and litter layer. Rainfall absorption occurred more at gentle slope, leading to higher SMC. Additionally, rainfall absorption was interpreted as being intercepted by the litter layer. Consequently, the correlation coefficient between SMC increment and rainfall was lower in the non-foliage season (R² = 0.37–0.56) than in the foliage season (R² = 0.72–0.84). With temporal progression, however, SMC response to rainfall increased where the litter was thickly accumulated, suggesting that litter interception was gradually diminished by decomposition. In this study, spatial heterogeneity in the litter layer and slope gradient substantially influenced the supply of soil moisture from rainfall.