A Study on the Status of Waterbirds in the Siheung Gaetgol Wetland (2020-2024)

Long-term monitoring data are essential for understanding the spatial and temporal variations of waterbird communities, particularly within rapidly changing urban wetland ecosystems. This study presents a standardized dataset of waterbird occurrences collected from Siheung Gaetgol Wetland, a designated Wetland Protected Area on the west coast of the Korean Peninsula. The dataset was compiled through a citizen–expert collaborative monitoring program conducted from 2020 to 2024. A total of 54 species and a cumulative number of 30,247 individuals were recorded across 20 surveys, and all observations were spatially referenced to six survey grids. The dataset includes key variables, such as survey date, survey effort, survey type, grid location, species name, and individual counts. Analysis of the compiled dataset revealed that waterbird assemblages were predominantly characterized by a small number of highly abundant species. The 10 most prevalent species accounted for over 95% of the total number of individuals observed. Among the various taxonomic groups, Anseriformes demonstrated the highest abundance across all grids and years among the various taxonomic groups, while Charadriiformes exhibited consistently high species richness among the various taxonomic groups. Spatial comparisons revealed clear heterogeneity. The central grid (D) had the highest species richness (33 species) and abundance (9,331 individuals). This likely reflects the area’s diverse habitat features, including open water, reed beds, and shallow tidal flats. Temporal variation in species richness showed interannual fluctuations, declining after 2020 and surging to a peak of 38 species in 2024. This dataset is valuable for providing baseline information for biodiversity assessments, habitat management, and long-term ecological monitoring. It is expected to lay the groundwork for future studies on species distribution dynamics, climate-driven changes, and wetland conservation planning.