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.

The occurrence of sudden strike pest events in urban areas is increasing as global warming intensifies, consequently, re causing harmful impacts. Studies on these incidents are fewer in number and insufficient compared to research on other nuisances such as mosquitoes and flies. Therefore, we conducted a study on the development of a selective collection method, using a filter layer to establish a monitoring system for Ephemera orientalis (Ephemeroptera: Ephemeridae), a species frequently identified as a sudden strike pest. Three sampling points were selected along the Hangang River in Namyangju, where E. orientalis outbreaks occur. Prototypes, consisting of four layers and with a light source attached to attract insects, were installed at each sampling point. Sampling was performed every 30 minutes between 19:00 and 22:30 in the month of June. The filter interval of each layer was adjusted so that the collected mayflies were distributed into specific layers. To evaluate the collection efficiency in line with the materials and the filter intervals, the optimal collection efficiency was investigated by combining two types of layer materials (stainless and acrylic) and filter intervals (1-5 mm). The optimal conditions were as follows: The selective collection efficiency was found to be highest at 96.5% when the interval of the selective target filter was 2.0 mm and there was one upper filter.

The bitterling (Cyprinidae, Acheilongnathinae) is a temperate freshwater fish with a unique spawning symbiosis with host mussels. Female bitterlings use their extended ovipositors to lay eggs on the gills of mussels through the mussel's exhalant siphon. In the present study, in April of 2020, we investigated spawning frequencies and patterns of three bitterling fish species in host mussel species in the Nakdong River basin (Hoecheon). During field surveys, a total of four bitterling and three mussel species were found. We observed bitterling's spawning eggs/larvae in the three mussel species: Anodonta arcaeformis (proportion spawned: 45.5%), Corbicula fluminea (12.1%), and Nodularia douglasiae (45.2%). The number of bitterlings’ eggs/larvae per mussel ranged from 1 to 58. Using our developed genetic markers, we identified the eggs/ larvae of each bitterling species in each mussel species (except for A. macropterus): A. arcaeformis (spawned by Acheilognathus yamatsutae), C. fluminea (A. yamatsutae and Tanakia latimarginata), and N. douglasiae (A. yamatsutae, Rhodeus uyekii, and T. latimarginata). Approximately 57.6% of N. douglasiae mussel individuals had eggs/ larvae of more than one bitterling species, suggesting that interspecific competition for occupying spawning grounds is intense. This is the first report on bitterling’s spawning events in the Asian clam C. fluminea from Korea; however, it should be ascertained whether bitterling’s embryo undergoes successful development inside the small mussel and leaves as a free-swimming juvenile. In addition, the importance of its conservation as a new host mussel species for bitterling fishes needs to be studied further.