Lentic ecosystems, including lakes, reservoirs, and marshes, are vital ecological assets increasingly threatened by anthropogenic pressures, necessitating robust tools for assessing their biological integrity. This study aimed to develop and apply an aquatic plant-based Multi-metric Index (MMI) to evaluate the biological integrity of 90 lentic systems (primarily lakes and reservoirs) across the Republic of Korea, using a standardized dataset from a three-year national monitoring program (2022~2024). We selected eight metrics based on their ecological relevance, sensitivity to disturbance, and scientific robustness. These were organized into three categories: Species richness (30% weight), eutrophication and disturbance (30%), and habitat integrity (40%). Scoring criteria for each metric were established using cumulative distribution functions, and the final MMI scores were used to classify the ecosystems into five integrity classes (A: Excellent to E: Very Poor). The assessment revealed that the majority of the surveyed ecosystems (87.8%) were in a moderate to slightly poor state (Classes B, C, and D), with only 4.4% classified as excellent. Widespread loss of submerged and floating leaved aquatic plants suggests that many domestic lentic systems may be approaching or have already undergone a regime shift to a turbid, phytoplankton-dominated state. This MMI provides a scientifically-defensible tool for managing lentic ecosystems, underscoring the urgent need to restore aquatic plants communities by improving underwater light conditions and rehabilitating littoral habitats.

This study was conducted to develop a fish-based Multi-metric Index (MMI) for assessing the ecological health of lake ecosystems using fish assemblage data collected from the national lake biomonitoring program between 2022 and 2024. A total of 34 fish assessment metrics widely used in the United States, Europe, and Korea were first reviewed for applicability, from which 16 candidate metrics were selected. These candidate metrics were then evaluated in terms of statistical distribution characteristics, correlations with water quality variables, redundancy among metrics, and consistency with existing river-based metrics used in Korea. Based on these evaluations, eight core indicators and four supporting indicators were finalized. For ecological health scoring, boundary values for metric scoring classes were determined using percentiles (10-25-50-75-90%), and metric weights were applied to ensure balanced contribution and discriminative power among classes. The final set of metrics consisted of three indicators in the Diversity/Richness category, two in the Trophic category, two in the Tolerance category, and one in the Individual Health category, collectively reflecting the ecological responses of fish assemblages in lake environments. The developed MMI framework is expected to provide a robust and applicable tool for future ecological assessments and management of lakes in Korea.

Zooplankton are dominant pelagic consumers in lake ecosystems with high population and biomass. Their broad geographical distribution, ease of quantification, and rapid responses to abiotic environmental factors, such as eutrophication, acidification, and climate change, make them highly suitable as indicator organisms for assessing lake ecosystem health. The multi-metric index (MMI) provides an effective framework for capturing the complex responses of biological communities to varying environmental stressors, making it a valuable approach for improving the practical effectiveness of lake ecosystem management based on biological assessments. This study introduces the Lake Zooplankton Assessment Index (LZAI), developed for 90 lakes in South Korea. The LZAI comprises four components: a sensitive species index based on cladocerans, a eutrophication index based on rotifers, a food web index based on copepods, and a habitat index based on species diversity. Applying the LZAI to 90 lakes showed that lake grades followed a normal distribution regardless of sampling season, though A-grade and E-grade lakes exhibited greater seasonal variability. When compared with the clustering results based on zooplankton community composition, the LZAI closely reflected the underlying patterns in community structure. However, in brackish lakes-where population densities are lower and Calanoida copepods dominate relative to freshwater lakes-the M1 and M4 indices were consistently low, while M2 and M3 were high. This suggests that the LZAI requires index adjustments tailored to regional and lake-type factors, including size, depth, and salinity. Incorporating biomass data into the index would further improve the accuracy of assessing community structure and its role in nutrient and energy cycling.

Recently, Korean government has introduced Multi Metric Indices (MMI) using various biocommunity information for aquatic ecosystem monitoring and ecosystem health assessment at the national level. MMI is a key tool in national ecosystem health assessment programs. The MMI consists of indices that respond to different target environmental factors, including environmental disturbance (e.g. nutrients, hydrological and hydraulic situation of site etc.). We used zooplankton community information collected from Korean lakes to estimate the availability of candidate zooplankton MMI indices that can be used to assess lake ecosystem health. First, we modified the candidate indices proposed by the U.S. EPA to suit Korean conditions. The modified indices were subjected to individual index suitability analysis, correlation analysis with environmental variables, and redundancy analysis among indices, and 19 indices were finally selected. Taxonomic diversity was suggested to be an important indicator for all three taxonomic groups (cladoceran, copepod, rotifer), on the other hand, the indices using biomass for large cladocerans and copepods, while the indices using abundance were suggested for small cladocerans and rotifers.