Anthropogenic activities, such as land use and land cover modifications in riparian areas, can alter the degree of fragmentation of riparian vegetation, lead to the degradation of stream habitats, and affect biological communities in the streams. The characteristics of the riparian forests can modify the condition of stream environments and the transporting mechanisms of materials, sediments, nutrients, and pollutants loaded from the watersheds. This study aimed to examine the relationships between forest fragmentation and three biological indicators of trophic diatom, benthic macroinvertebrate, and the fish assessment in the Nakdong River, Korea. Eighty-nine biological assessment sampling sites in the National Aquatic Ecological Monitoring Program of South Korea were identified. For each sampling site, riparian forest data within a 500 m radius were extracted from national LULC using GIS to compute fragmentation metrics using FRAGSTATS software. Four fragmentation metrics—number of forest patches, percentage of riparian forest cover (PLAND), largest riparian forest patch index (LPI), and riparian forest division index (DIVISION)—were correlated with the biological indicators. Also, due to severe spatial autocorrelation among observations, the fragmentation metrics and stream environmental variables were regressed to biological indicators using regression tree analysis. Our results indicate that the biological indicators were significantly associated with most forest fragmentation metrics. We found positive correlations of PLAND and LPI with biological indicators, whereas DIVISION was negatively correlated with biological indicators. Both correlation and regression tree analyses revealed that the biological conditions of streams were likely to be better if riparian forests are less fragmented. Particularly, stronger relationships were revealed between macroinvertebrates and fish with the fragmentation metrics of riparian forests than with benthic diatoms. However, these relationships varied with elevation, stream size, and slope conditions. The results of this study reinforced the importance of including riparian forests in the planning, restoration, and management of stream environments. These results also suggested that planners and managers may need to consider different strategies for different stream environments and topographic characteristics in managing riparian forests.

Understanding the relation between watershed land use and stream conditions is critical for watershed planning and management. This study investigated the effects of land use on stream water quality and biological conditions in sub-watersheds and micro-watersheds across the Han River watershed in South Korea. We developed random forest models for each water quality and biological indicator using the proportions of urban, agricultural, and forested areas. Our results indicate that water quality and biological indicators were significantly affected by forest area at both scales, and the sub-watershed models performed better than the micro-watershed models. Accumulated local effects were used to interpret the effect of each explanatory variable on the response variable. The plots for water quality and biological indicators with proportions of watershed land use demonstrated similar patterns at both scales, although the relation between land use and stream conditions was slightly more sensitive in micro-watersheds than in sub-watersheds. Urban and agricultural areas showed a lower proportion of water quality and biological condition variability in the micro-watersheds than in the sub-watersheds, while forests showed the opposite results. The findings of this study suggest that different spatial scales should be considered when developing effective watershed management strategies to maintain stream ecosystems.

Understanding the responses of stream ecosystems to environmental disturbances is essential for maintaining and restoring healthy ecosystems. In this study, we analyzed the associations between benthic macroinvertebrate communities and environmental factors using machine learning approaches to identify key stressors potentially influencing stream ecosystem health. Various machine learning models were evaluated, with random forest (RF) and gradient boosting machine (GBM) identified as the optimal models for predicting tolerant species (TS) and Ephemeroptera, Plecoptera, and Trichoptera (EPT) species densities. SHAP analysis revealed that watershed variables, such as elevation, flow velocity, and slope, significantly influenced EPT and TS populations. EPT population density increased with elevation and flow velocity but decreased significantly with higher levels of biochemical oxygen demand (BOD), total nitrogen (TN), and agricultural land-use proportions, with negative effects becoming evident beyond threshold levels. Conversely, TS population density showed a positive response to elevated BOD, TN, and agricultural land-use proportions, stabilizing at the threshold levels of BOD and TN, but continuing to increase with greater agricultural land use. Through machine learning, this study provides critical insights into how environmental variables are associated with the distribution of benthic macroinvertebrate communities. By identifying threshold levels of key stressors, this approach offers actionable guidance for managing agricultural runoff, enhancing riparian buffers, and implementing sustainable land-use practices. These findings contribute to the development of integrated watershed management strategies that promote the long-term sustainability of stream ecosystems.

The objective of this study was to determine the effect of prior knowledge and visual evaluation on supports for rain garden installations. To achieve this objective, a survey was conducted to obtain prior knowledge of rain gardens, rain garden implementation support ratings, and visual evaluation of rain gardens in 100 visitors of three rain garden sites. Results of the analysis revealed that users’ visual evaluation of rain gardens played a role as a moderator in the relationship between prior knowledge and support for rain garden installations. In other words, education and publicity of rain gardens alone cannot increase support for rain gardens. However, if rain gardens are visually evaluated positively, the effects of education and publicity of rain gardens can be expected. Therefore, to successfully apply a rain garden policy in the future, basic consideration should be given to aesthetics in order to meet visitors’ visual expectations prior to education and publicity of rain gardens.