Odonata species are sensitive to environmental changes, particularly those caused by humans, and provide valuable ecosystem services as intermediate predators in food webs. We aimed: (i) to investigate the distribution patterns of Odonata in streams on a nationwide scale across South Korea; (ii) to evaluate the relationships between the distribution patterns of odonates and their environmental conditions; and (iii) to identify indicator species and the most significant environmental factors affecting their distributions. Samples were collected from 965 sampling sites in streams across South Korea. We also measured 34 environmental variables grouped into six categories: geography, meteorology, land use, substrate composition, hydrology, and physicochemistry. A total of 83 taxa belonging to 10 families of Odonata were recorded in the dataset. Among them, eight species displayed high abundances and incidences. Self-organizing map (SOM) classified sampling sites into seven clusters (A–G) which could be divided into two distinct groups (A–C and D–G) according to the similarities of their odonate assemblages. Clusters A–C were characterized by members of the suborder Anisoptera, whereas clusters D–G were characterized by the suborder Zygoptera. Non-metric multidimensional scaling (NMDS) identified forest (%), altitude, and cobble (%) in substrata as the most influential environmental factors determining odonate assemblage compositions. Our results emphasize the importance of habitat heterogeneity by demonstrating its effect on odonate assemblages.

Numerous community indices have been developed to quantify the various aspects of communities. However, indices including functional aspects have been less focused on. Here, we examined how community composition varies in response to the environment and discovered the relationship between taxonomic diversity and functional diversity while considering the environment. Macroinvertebrate communities were collected from 20 reservoirs in South Korea. To characterize functional diversity, functional traits in four categories were considered: generation per year, adult lifespan, adult size, and functional feeding groups. Based on their community composition, we classified the reservoirs using hierarchical cluster analysis. Physicochemical and land use variables varied considerably between clusters. Non-metric multidimensional scaling indicated differences between reservoirs and clusters in terms of structure, functional diversity, and environmental variables. A self-organizing map was used to categorize functional traits, and network association analysis was used to unravel relationships between functional traits. Our results support the characteristics of species’ survival strategies such as r- and K-selection. Functional richness exhibited a relationship with taxonomic diversity. Our findings suggest that different types of diversity could play complementary roles in identifying biodiversity. Our findings should prove useful in developing new criteria for assessing freshwater ecosystem health, as well as in evaluating and predicting future alteration of benthic macroinvertebrate communities facing anthropogenic disturbances.

Functional traits are the result of evolution and adaptation, providing important ecological insights into how organisms interact with their environment. Benthic macroinvertebrates, in particular, have garnered attention as biomonitoring indicators for freshwater ecosystems. This study presents a functional trait dataset for benthic macroinvertebrates, comprising 447 taxa (393 at genus level, 53 at family level and one at class level) from five phyla (Annelida, Arthropoda, Mollusca, Nematomorpha, and Platyhelmenthes), categorized into nine traits related to life history, morphology, and habit. To account for variation in available trait information, we assigned confidence levels to each taxon and functional trait based on the level of evidence using fuzzy coding. Our dataset provides an important resource for understanding the ecology of benthic macroinvertebrates in South Korea, serving as a valuable baseline dataset for studying their biodiversity, conservation, and biomonitoring in freshwater ecosystems.

Motivation: The metaweb is a dictionary of nodes and their potential interactions developed for a particular region, focusing on a particular type of ecosystem. Based on the local biodiversity information at different spatial and temporal scales, the regional metaweb can be easily decomposed into local webs. The generated local webs are useful for understanding spatiotemporal variations in ecological interactions in a particular region. In this study, an attempt was made to develop a trophic metaweb for freshwater ecosystems in South Korea, called the KF‐metaweb. The metaweb contains 23,074 interactions between 446 taxa collected from 730 studies. This metaweb can be used to understand the spatiotemporal variability of different local food webs and the effects of the environment on food web properties. Furthermore, this is the first metaweb developed for any Asian ecosystem that contains information about many interactions that are unavailable in any other existing database. In addition, this metaweb study enriches our global understanding of ecological interactions.Main Types of Variables Contained: The data contained trophic interactions between resources (prey) and consumers (predators).Spatial Location and Grain: The mainland of South Korea and Jeju Island.Time Period and Grain: 2008–2021.Major Taxa: Microalgae (belonging to the phyla Cyanobacteria, Bygra, Cryophyta, Myozoa, Ochrophyta, Charophyta, Chlorophyta, Euglenozoa and Mycetozoa), zooplankton (belonging to the phyla Arthropoda and Rotifera), benthic macroinvertebrates (Platyhelmenthes, Annelida, Arthropoda and Mollusca) and fish.Level of Measurement: Minimum taxonomic resolution was at the genus level for fish and benthic macroinvertebrates and order level for zooplankton and microalgae.Software Format: Excel (*.xlsx).

Reservoir ecosystems play a critical role in supporting ecological functions but are highly vulnerable to fluctuations in inflow characteristics and pollutant accumulation, often resulting in food web disruption and ecological imbalance. Therefore, ecosystem-based management that integrates ecological processes and food web dynamics is increasingly emphasized. In this study, the Delft3D hydrodynamic model and the AQUATOX food web model were coupled to simulate biomass dynamics in the Singal Reservoir, Republic of Korea, under varying environmental conditions. Delft3D was used to generate high-resolution hydrodynamic and water quality data, which served as input for AQUATOX to simulate ecological responses to 3 management scenarios, such as dredging sediment and increased and reduced nutrient inflows. AQUATOX successfully reproduced biomass fluctuations observed in field surveys and provided realistic simulations of ecosystem structural responses. Sensitivity analysis revealed key environmental variables that influence biomass across different taxonomic groups, and highlighted competitive interactions among species that share common food resources. Scenario simulations demonstrated that nutrient reduction resulted in the most substantial biological improvements, whereas increased nutrient loading amplified biomass of blue-green algae and intensified ecological instability. The integrated use of Delft3D and AQUATOX enhanced observational capacity and enabled detailed exploration of ecological response mechanisms under diverse disturbance scenarios. Although continuous monitoring data and parameter optimization remain challenging aspects, the coupled model framework proved effective for reservoir ecosystem assessment. The findings offer practical insights for predicting ecological responses and guiding ecosystem-based reservoir management strategies.