Almost all of the water from agricultural dams located to the upper of the Yeongsan river is supplied as irrigation water for farmland and thus is not discharged to the main stream of the river. Also, most of the irrigation water does not return to the river after use, adding to the lack of flow in the main stream. As a result, the water quality and aquatic health of the river have become the poorest among the four major rivers in Korea. Therefore, in this study, several strategies for water quality improvement of the river were developed considering pollution reduction and flow rate increase, and their effect analysis was performed using a water quality model. The results of this study showed that the target water quality of the Yeongsan river could be achieved if flow increase strategies (FISs) are intensively pursued in parallel with pollution reduction. The reason is because the water quality of the river has been steadily improved through pollution reduction but this method is now nearing the limit. In addition, rainfall-related FISs such as dam construction and water distribution adjustment may be less effective or lost if a megadrought continues due to climate change and then rainfall does not occur for a long time. Therefore, in the future, if the application conditions for the FISs are similar, the seawater desalination facility, which is independent of rainfall, should be considered as the priority installation target among the FISs. The reason is that seawater desalination facilities can replace the water supply function of dams, which are difficult to newly build in Korea, and can be useful as a climate change adaptation facility by preventing water-related disasters in the event of a long-term megadrought.
Benthic attached diatoms (BADs), a major primary producer in lotic stream and river ecosystems are micro-sized organisms and require a highly magnified microscopic technique in the observation work. Thus, it is often not easy to ensure accuracy and precision in both qualitative and quantitative analyses. This study proposed a new technique applicable to improve quality control of aquatic ecosystem monitoring and assessment using BADs. In order to meet the purpose of quality control, we developed a permanent mounting slide technique which can be used for both qualitative and quantitative analyses simultaneously. We designed specimens with the combination of grid on both cover and slide glasses and compared their efficiency. As a result of observation and counting of BADs, the slide glass designed with the color-lined grid showed the highest efficiency compared to other test conditions. We expect that the method developed in this study could be effectively used to analyze BADs and contributed to improve the quality control in aquatic ecosystem health monitoring and assessment.
This study was conducted to investigate the current status of seagrass species in the Nakdong River estuary from May to June 2023. To survey the seagrass habitat area, the Nakdong River estuary was divided into seven zones. Aerial photography using drones was conducted to find seagrass areas, GPS tracking was carried out on foot in the intertidal zone and by boat and SCUBA diving in the subtidal zone. To analyze the seagrass status, we measured the morphological characteristics, shoot density, and biomass of representative seagrass species in each zone. Four seagrass species were found in this area: Zostera japonica, Z. marina, Ruppia maritima, and Phyllospadix japonicus. The distribution areas of each species was 338.2 ha, 92.9 ha, 0.9 ha, and 1.4 ha, respectively, with a total area of 432.5 ha. Z. japonica was widely distributed in most of the tidal flats and mudflats of the Nakdong River estuary, while Z. marina was restricted to Nulcha-do, Jinu-do, and Dadae-dong. R. maritima occurred within the habitat of Z. japonica in Eulsukdo and Myeongji mudflats, and P. japonicus inhabited rocky areas in Dadae-dong. The shoot density of each species was 4,575.8±338.3 shoots m-2, 244.8±12.0 shoots m-2, 11,302.1±290.0 shoots m-2, and 2862.5±153.5 shoots m-2, respectively. The biomass of each species was 239.7±18.5 gDW m-2, 362.3±20.5 gDW m-2, 33.3±1.2 gDW m-2, and 1,290.0±37.0 gDW m-2, respectively. The results of this study revealed that Z. japonica was dominant in the Nakdong River estuary. In particular, Z. japonica habitats of Eulsukdo, Daema-deung, and Myeongji mudflats were identified as the largest in Korea. The Nakdong River estuary is an important site of ecological, environmental, and economic value, and will require continuous investigation and management of the native seagrasses.
Invasive predators are one of the most damaging species groups to biodiversity. In the Nakdong River, the lake skygazer Chanodichthys erythropterus is a dominant species that is fiercely carnivorous and a concern for commercial fish. Although it is important to understand the ecological characteristics related to the feeding habit, studies on the diets of lake skygazer in Nakdong River have been limited to studies of gut contents. In this study, the trophic position (TP) and feeding habits of C. erythropterus were studied by calculating TPs using samples collected from 13 sites throughout the Nakdong River. Compound-specific isotopic analysis of amino acids provided reliable TPs from the muscle of Lake skygazer C. erythropterus without any isotope baseline. The results were approximately 3 to 3.6 and suggesting a carnivorous but size-dependent prey variation. In particular, the TP variability of C. erythropterus observed in the Nakdong River showed that it had a selective feeding habit compared to carnivorous fish species of relatively similar trophic levels.
Microphysogobio rapidus is designated as endangered species class I by Ministry of Environment, and its distribution and population have been gradually declining, and it is now limited to the Nam River and some tributary streams of the Nakdong River Watershed. For the restoration of this highly endangered species, it is important to identify the causes of the decline and establish appropriate restoration plans. However, due to lack of basic data and ecological research, most steps are stagnant. Therefore, in this study, we identified the differences in the physical, biological, and sociological habitats between current and past distributed sites through field surveys and literature reviews. As a result of the field survey, there were differences in conductivity between the current and past distributed sites, and fish communities were also showed differences. The literature data also showed that the physico-chemical values of the past distributed sites were generally unfavorable, which generated negative consequences on biological factors. In particular, the effects of urbanization were found to be a major factor affecting the habitat of M. rapidus. Habitat stabilization is crucial for the recovery of this endangered species. However, in the past distributed sites, disturbances such as stream development and weir construction have altered streams physico-chemically and result in changes of M. rapidus. Therefore, a comprehensive plan that considers both stream connectivity and water quality is needed to manage and restore the habitat of M. rapidus.
The aquarium pet trade is a source of potentially invasive crayfish species, which can be subsequently intentionally or unintentionally introduced into new environments. There were 34 species of freshwater crayfish imported into Korea for ornamental purposes. Starting with 1 species in 2008, it shows a trend of continuous increase every year with the maximum of 25 species in 2020. The number of freshwater crayfish imported into Korea for ornamental purposes was 1,172,159, with an annual average of 78,144 being imported. The population also recorded a record high in 2017 with a 38% increase in population imports compared to the previous year. Among the 34 pet crayfish imported into Korea, four species classified as high-risk and managed in the US and Europe were American crayfish (Procambarus clarkii), Cherax quadricarinatus, Cherax cainii, and Cherax destructor. In addition to American crayfish (P. clarkii), 3 types of high-risk invasive crayfish are designated as legally managed species by conducting an ecological risk assessment, raising awareness among importers, retailers and consumers through awareness-raising education on freshwater crayfish, and measures for route management such as species identification and improvement of labeling methods are needed.
Freshwater jellyfish, a type of jellyfish exclusively found in freshwater, has a limited number of species but is found globally. However, their ecology and causes of occurrence are largely unknown. Therefore, understanding the distribution of polyps, which produce the larvae of freshwater jellyfish, can provide important data for comprehending their ecology. This study aims to explore the COI gene of freshwater jellyfish using environmental DNA from the microbial film in the Miho River system. Among the 12 survey points in the Miho River watershed, genetic material of freshwater jellyfish was detected in 8 points, mainly located upstream near reservoirs. These genetic materials were identified as genes of the well-known freshwater jellyfish species, Craspedacusta sowerbii. Notably, the C. sowerbii genes found in the Miho River watershed survey points were closely related to a species previously discovered in Italy. Consequently, utilizing environmental DNA to explore the genetic traces of freshwater jellyfish enables rapid screening of areas with a high likelihood of freshwater jellyfish occurrence. This approach is deemed to provide crucial information for understanding the distribution and ecology of freshwater jellyfish in Korea.
This study analyzed the relationship between distribution of Bolboschoenus planiculmis which is main food source of swans (national monument species) with environmental factors, discharge, rainfall, and salinity in Eulsuk-do from 2020 to 2023. The distribution area of B. planiculmis in Eulsuk tidal flat was 103,672 m2 in 2020, 95,240 m2 in 2021, 88,163 m2 in 2022, and 110,879 m2 in 2023, and represents a sharp decrease compared to the 400,925 m2 area recorded in 2004. From 2020 to 2023, the growth densities of B. planiculmis were 243.6±12.5 m-2, 135.45±7.38 m-2, 51.10±2.54 m-2, and 238.20±16.36 m-2, respectively, and the biomass was 199.89±28.01 gDW m-2, 18.57±5.12 gDW m-2, 6.55±1.12 gDW m-2, and 153.53±25.43 gDW m-2 in 2020, 2023, 2021, and 2022, respectively. Based on discharge during May~July, which affects plant growth, the left gate discharge of the estuary barrage from 2020 to 2023 was 62,322 m3 sec-1, 33,329 m3 sec-1, 6,810 m3 sec-1, and 93,641 m3 sec-1, respectively; rainfall was 1,136 mm, 799 mm, 297 mm, and 993 mm, respectively; and average salinity was 14.7±9.4 psu, 21.1±4.7 psu, 26.1±2.7 psu, and 14.5± 11.1 psu, respectively. In 2022, cumulative rainfall (978 mm, about 70% of the 30-year average) and discharge (43,226 m3 sec-1) decreased sharply, resulting in the highest mean salinity (25.46 psu), and the distribution area, density, and biomass of the B. planiculmis decreased sharply. In 2023, there was a rise in discharge with an increase in rainfall, leading to a decrease in salinity. Consequently, this environmental change facilitated the recovery of B. planiculmis growth.
Nowadays, artificial intelligence model approaches such as machine and deep learning have been widely used to predict variations of water quality in various freshwater bodies. In particular, many researchers have tried to predict the occurrence of cyanobacterial blooms in inland water, which pose a threat to human health and aquatic ecosystems. Therefore, the objective of this study were to: 1) review studies on the application of machine learning models for predicting the occurrence of cyanobacterial blooms and its metabolites and 2) prospect for future study on the prediction of cyanobacteria by machine learning models including deep learning. In this study, a systematic literature search and review were conducted using SCOPUS, which is Elsevier’s abstract and citation database. The key results showed that deep learning models were usually used to predict cyanobacterial cells, while machine learning models focused on predicting cyanobacterial metabolites such as concentrations of microcystin, geosmin, and 2-methylisoborneol (2-MIB) in reservoirs. There was a distinct difference in the use of input variables to predict cyanobacterial cells and metabolites. The application of deep learning models through the construction of big data may be encouraged to build accurate models to predict cyanobacterial metabolites.