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Faecal contamination is a widespread environmental and public health problem on recreational beaches around the world. The implementation of predictive models has been recommended by the World Health Organization as a complement to traditional monitoring to assist decision-makers and reduce health risks. Despite several advances that have been made in the modeling of faecal coliforms, tools and algorithms from machine learning are still scarcely used in the field and their implementation in nowcast systems is delayed. Here, we perform a literature review on modeling strategies to predict faecal contamination in recreational beaches in the last two decades and the implementation of models in nowcast systems to aid management. Models constructed for surface waters of continental (lakes, rivers and streams), estuarine and marine coastal ecosystems were analyzed and compared based on performance metrics for continuous (i.e. regression; R 2 , Root Mean Square Error: RMSE) and categorical (i.e. classification; accuracy, sensitivity, specificity) responses. We found 67 articles matching the search criteria and 40 with information allowing to evaluate and compare predictive ability. In early 2000, Multiple Linear Regressions were common, followed by a peak of Artificial Neural Networks (ANNs) from 2010 to 2015, and the rise of Machine learning techniques, such as decision trees (CART and Random Forest) since 2015. ANNs and decision trees presented better accuracy than the remaining models. Rainfall and its lags were important predictor variables followed by water temperature. Specificity was much higher than sensitivity in all modeling strategies, which is typical in data sets where one category (e.g. closed beach) is far less common than the normal state (i.e. unbalanced data sets). We registered the implementation of statistical models in early warning systems in 6 countries, mainly by public beach quality management institutions, followed by NGOs in conjunction with universities. We identified critical steps towards improving model construction, evaluation and usage: i) the need to balance the data set previous to model training, ii) the need to separate data set in training, validation and test to perform an honest evaluation of model performance and iii) the transduction of model outputs to plain language to relevant stakeholders. Integrating into a single framework in situ monitoring, model construction and nowcasting systems could help to improve decision making systems to protect users from bathing in contaminated waters. Still the reduction of arrival of faecal coliforms to aquatic ecosystems (e.g. by improving sewage treatment systems) will be the ultimate factor in reducing health risk., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Cyanobacterial toxic blooms are a worldwide problem. The Río de la Plata (RdlP) basin makes up about one fourth of South America areal surface, second only to the Amazonian. Intensive agro-industrial land use and the construction of dams have led to generalized eutrophication of main tributaries and increased the intensity and duration of cyanobacteria blooms. Here we analyse the evolution of an exceptional bloom at the low RdlP basin and Atlantic coast during the summer of 2019. A large array of biological, genetic, meteorological, oceanographic and satellite data is combined to discuss the driving mechanisms. The bloom covered the whole stripe of the RdlP estuary and the Uruguayan Atlantic coasts (around 500 km) for approximately 4 months. It was caused by the Microcystis aeruginosa complex (MAC), which produces hepatotoxins (microcystin). Extreme precipitation in the upstream regions of Uruguay and Negro rivers' basins caused high water flows and discharges. The evolution of meteorological and oceanographic conditions as well as the similarity of organisms' traits in the affected area suggest that the bloom originated in eutrophic reservoirs at the lower RdlP basin, Salto Grande in the Uruguay river, and Negro river reservoirs. High temperatures and weak Eastern winds prompted the rapid dispersion of the bloom over the freshwater plume along the RdlP northern and Atlantic coasts. The long-distance rapid drift allowed active MAC organisms to inoculate freshwater bodies from the Atlantic basin, impacting environments relevant for biodiversity conservation. Climate projections for the RdlP basin suggest an increase in precipitation and river water flux, which, in conjunction with agriculture intensification and dams' construction, might turn this extraordinary event into an ordinary situation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Environmental sustainability of South American rainfed agroecosystems is of current concern. In this work, we evaluate the occurrence of multiple pesticide residues in muscle tissue of wild fish species from two large rivers in South America (Uruguay and Negro Rivers). Two sampling campaigns (representing summer and winter crops) were performed during 2015 targeting a wide biodiversity of fish species used for human consumption (ranging from migratory to non-migratory and from detritivorous to top-predators). Three different localities associated to rainfed agriculture were assessed, two of them enclosed to a RAMSAR site (National Park "Esteros de Farrapos e Islas del Rio Uruguay"). Pesticide residues occurred in muscle tissue of 143 from 149 sampled fishes (96%). Thirty different pesticides were detected at concentrations from <1 to 194μgkg -1 . Incidence of pesticides in fish were tightly related to: i) features of the contaminant: (Kow, environmental persistence and mobility) and ii) intensity of use of particular pesticides and land dedicated to rainfed agriculture. Trifloxystrobin, metolachlor and pyraclostrobin showed the highest rates of occurrence. Of great concern is that strobirulins have highest toxicity to fish from those detected compounds. From the pattern of pesticides occurring for non-migratory fish species it was possible to trend important spatial differences related to the intensity of rainfed agriculture. Results suggest a regular exposition of aquatic wild biota to sublethal concentrations of multiple semi-polar pesticides., (Copyright © 2018 Elsevier B.V. All rights reserved.)