Understanding the relationship between benthic macroinvertebrates and environmental variables is the first step toward establishing sustainable freshwater ecosystems in terms of biodiversity, and this knowledge can be applied in river management. We analyzed major environmental variables that affect biotic communities on the national scale in the Republic of Korea. To achieve this goal, 2647 sampling stream sites were surveyed from 2016 to 2018 to collect benthic macroinvertebrates and measure 14 environmental variables. We identified a total of 359 taxa, belonging to 32 orders in 9 classes of 5 phyla, most of which were aquatic insects including Ephemeroptera, Odonata, Plecoptera, Coleoptera, Diptera and Trichoptera. Two-way indicator species analysis (TWINSPAN) based on biotic communities divided the sampling sites into six groups. Discriminant analysis identified gradient, streambed substrates, velocity, biological oxygen demand (BOD) and altitude as the major environmental variables that distinguished each TWINSPAN group. In addition, stream order and stream width also influenced aquatic macroinvertebrate communities, but the influence was low. The indicator taxa in each group were gradually changed from sensitive organisms preferring high altitudes, fast velocities and coarse substrates to tolerant organisms preferring low altitudes, slow velocities and fine substrates in each group from one to six. Canonical correspondence analysis confirmed that the composition of benthic macroinvertebrate communities in the Republic of Korea was dependent on stream gradient, microhabitat, organic pollution and geographical feature rather than on stream size or other water quality variables. Our study identified variables affecting the overall distribution patterns of biotic communities on a national scale and provides useful information for conservation and management of stream ecosystems in the Asian monsoon region.

Benthic macroinvertebrate functional feeding groups (FFGs) are influenced by the availability of food sources, which can be affected by stream size and gradient. We investigated the spatial distribution patterns of FFGs by stream size (stream order, catchment area and stream width) and gradient (altitude and slope). In addition, we attempted stream classification based on the distribution patterns of FFGs. To achieve these goals, a total of 996 sampling sites of national scale located in the Republic of Korea were investigated from 2008 to 2016. Among the five physical variables, stream width and slope showed linear relationships with the indicator values of FFGs. These two physical variables had larger influences on the distribution of FFGs compared to other variables. Geology (the type of rocks) showed little influences on the distribution of benthic macroinvertebrate communities. We classified streams focusing on catchment (stream size) area and altitude (stream gradient) because they are constants that do not change with disturbances. The FFGs and benthic macroinvertebrate assemblages were distinctly changed by stream types, indicating that the stream classification criterion adequately represented changes in physical variables in biotic terms. In addition, the distribution of FFGs and biotic assemblages showed that benthic macroinvertebrates in the Republic of Korea were more influenced by the altitude (stream gradient) than the catchment area (stream size). In overall, this study found that the stream size and gradient markedly influence the distribution of FFGs in national regions of the Republic of Korea. Further research is needed focusing on the level of microhabitats and other parameters to identify the promising variables that influence biotic distribution.

Predictive models for the benthic macroinvertebrate community based on environmental variables facilitate the identification of the organisms expected to inhabit an area according to the target environmental conditions when restoring rivers. In this investigation, a biotic community predictive model was developed using benthic macroinvertebrate and environmental variable data collected from 1,210 sites in the Republic of Korea from 2010 to 2020. The sites were classified into six groups according to Two Way Indicator Species Analysis (TWINSPAN) and based on their individual abundance/m² of benthic macroinvertebrates. The TWINSPAN groups were related to 14 variables by stepwise multi-discriminant analysis. The relative importance of the environmental variables that classified each TWINSPAN group was in the order of mean diameter of particle size, catchment area, altitude, velocity, total phosphorus, latitude, pH, longitude, conductivity, water depth, suspended solids, biochemical oxygen demand, stream order, and total nitrogen. Discriminant functions 1–4 showed statistically significant and a predictive model was developed using functions 1 and 2 based on Wilks’ lambda values. The fit of the derived model was confirmed using Sørensen similarity (number of taxa) and Bray–Curtis dissimilarity (individual abundance/m²) analyses between the predicted organisms and those observed at the sites. The distributions of similarity and dissimilarity that were confirmed by stream type ranged from 0.60 to 0.72 and 0.46–0.56, respectively, based on the mean. Based on the predicted and observed values, the ratio of shredders and scrapers to collectors showed similar results overall for each stream type. The predictive model derived using nationally managed available data is expected to be applicable to stream and river restorations in the future, as it provides a statistical assessment of the biotic communities that are expected to inhabit a given environment.

Predictive models for benthic macroinvertebrates based on changes in environmental variables can assess the biological integrity of streams by comparing observed biotic communities with those expected at reference sites. To develop a predictive model of the abiotic community, we used benthic macroinvertebrates and environmental variables collected from 2,700 sites from 2010 to 2019. First, we selected 357 reference sites by using the 5-day biochemical oxygen demand, ammonia nitrogen, total phosphorus, turbidity, and coarse particle percentage. Then, we used Two-Way Indicator Species Analysis to classify the reference sites into six groups based on benthic macroinvertebrates. Reference sites classified by biological characteristics were linked to environmental variables by multi-discriminant analysis. The relative influences environmental variables on the classified groups were in decreasing order of catchment area, latitude, velocity, water depth, altitude, and longitude. To develop the predictive model, we combined (1) identification level, (2) grouping method, and (3) probability of capture, and then used the normalized root mean square error (NRMSE) to check the fit of each model. The higher the probability of capture was at the family level compared to the species level, the lower was the NRMSE. The grouping method was not as consistent as the identification level and probability of capture because the NRMSE for the number of taxa was low when used as a weighted average. The NRMSE was also low for the Benthic Macroinvertebrates Index and the Benthic Macroinvertebrates Family-level Biotic Index (BMFI) when used for assignment to the group with the highest probability. We selected the predictive model which used family level, weighted average, and BMFI-proposed indicator taxa as the final assessment model due to its sensitivity and fit. This model was the most reasonable choice, but we had to reduce the error of the model and revise it elaborately by securing additional environmental variables.

In 2011, Korea installed artificial structures on four rivers to secure water resources and reduce flood damage; however, these structures have altered ecosystems and aquatic communities. This study analyzed fish communities and environmental variables at 72 sites in the Geumgang River. Fish communities and environmental variables before weir installation were examined using site data from 2008 to 2009. The results showed that Cyprinidae dominated the 70 observed species. A self-organizing map categorized the 72 sites into four groups based on fish communities. Sensitive and insectivorous species decreased, whereas tolerant and omnivorous species increased from Groups I to IV. Twenty-one indicator species were identified, with fewer and less distinct distribution patterns in Groups II and III than in Groups I and IV. The fish assessment index (FAI) showed a decline in grades A and B and an increase in grades C and D from Groups I to IV. Correlation analysis between the FAI and environmental variables indicated that fish communities in the Geumgang River were mainly influenced by water quality, reflecting altitude gradients and pollution levels. This study’s findings are anticipated to significantly inform water management strategies for the Geumgang, Yeongsangang, Nakdonggang, and Hangang Rivers.