Data from: Cyanobacterial blooms in subtropical riverine and estuarine ecosystems of South America

Water quality impairment caused by toxic cyanobacterial blooms is a growing global concern adversely affecting the biodiversity and functioning of aquatic ecosystems, which can disrupt recreation and human health. Recent studies indicate that factors such as eutrophication, dam construction, and climate change are likely to increase the frequency and intensity of these blooms in aquatic ecosystems worldwide. This trend raises concerns in the subtropical South America (SA) region, where the pampas ecosystem has registered a sustained increase in the surface used by agroindustrial activities which leads to eutrophication of the Uruguay River (UR) and the Río de la Plata estuary (RdlP) ecosystems. The UR-RdlP system is crucial for recreational activities and serves as an essential water source. Historical monitoring data indicate that currently, toxic blooms are often documented in the UR and transported downstream to the RdlP (Kruk et al., 2017; Martínez de la Escalera et al., 2017). In this context, it is imperative to develop comprehensive and coherent reviewed datasets to analyze the spatio-temporal dynamics of toxic cyanobacterial blooms effectively. Despite the availability of public information, its accessibility and suitability for analysis are not always guaranteed. Therefore, establishing and maintaining comprehensive long-term databases in ecosystems frequented for recreational purposes is crucial for studying the mechanisms associated with bloom formation and predicting human health risks. Here, we provide historical records (1963-2022) and indices of toxic cyanobacterial blooms at ca. 80 sites in the subtropical region along the Uruguay River (UR) and Río de la Plata (RdlP). The data compilation process involved gathering dispersed information from open sources, research projects, reports from multiple water quality monitoring programs, and collaborative efforts with research institutions in the country and the region. Data was checked for consistency and included geospatial data on cyanobacterial cell abundance, microcystin concentration, chlorophyll-a concentration, and risk levels from field samples combined with relevant environmental, land use, and climatic variables. This included in-situ measured environmental variables (e.g., water temperature, salinity, turbidity, conductivity) and regional climate and hydrology information (e.g., precipitation and flow rates), as well as land use patterns in the UR basin (e.g., crops, forestation, gra