Cyanobacterial bloom monitoring and assessment in Latin America.

Cyanobacterial blooms have serious adverse effects on human and environmental health. In Latin America, one of the main world's freshwater reserves, information on this phenomenon remains sparse. To assess the current situation, we gathered reports of cyanobacterial blooms and associated cyanotoxins in freshwater bodies from South America and the Caribbean (Latitude 22° N to 45° S) and compiled the regulation and monitoring procedures implemented in each country. As the operational definition of what is a cyanobacterial bloom remains controversial, we also analyzed the criteria used to determine the phenomena in the region. From 2000 to 2019, blooms were reported in 295 water bodies distributed in 14 countries, including shallow and deep lakes, reservoirs, and rivers. Cyanotoxins were found in nine countries and high concentrations of microcystins were reported in all types of water bodies. Blooms were defined according to different, and sometimes arbitrary criteria including qualitative (changes in water color, scum presence), quantitative (abundance), or both. We found 13 different cell abundance thresholds defining bloom events, from 2 × 103 to 1 × 107 cells mL-1. The use of different criteria hampers the estimation of bloom occurrence, and consequently the associated risks and economic impacts. The large differences between countries in terms of number of studies, monitoring efforts, public access to the data and regulations regarding cyanobacteria and cyanotoxins highlights the need to rethink cyanobacterial bloom monitoring, seeking common criteria. General policies leading to solid frameworks based on defined criteria are needed to improve the assessment of cyanobacterial blooms in Latin America. This review represents a starting point toward common approaches for cyanobacterial monitoring and risk assessment, needed to improve regional environmental policies.

Nutrients and not temperature are the key drivers for cyanobacterial biomass in the Americas.

Cyanobacterial blooms imperil the use of freshwater around the globe and present challenges for water management. Studies have suggested that blooms are trigged by high temperatures and nutrient concentrations. While the roles of nitrogen and phosphorus have long been debated, cyanobacterial dominance in phytoplankton has widely been associated with climate warming. However, studies at large geographical scales, covering diverse climate regions and lake depths, are still needed to clarify the drivers of cyanobacterial success. Here, we analyzed data from 464 lakes covering a 14,000 km north-south gradient in the Americas and three lake depth categories. We show that there were no clear trends in cyanobacterial biomass (as biovolume) along latitude or climate gradients, with the exception of lower biomass in polar climates. Phosphorus was the primary resource explaining cyanobacterial biomass in the Americas, while nitrogen was also significant but particularly relevant in very shallow lakes (< 3 m depth). Despite the assessed climatic gradient water temperature was only weakly related to cyanobacterial biomass, suggesting it is overemphasized in current discussions. Depth was critical for predicting cyanobacterial biomass, and shallow lakes proved more vulnerable to eutrophication. Among other variables analyzed, only pH was significantly related to cyanobacteria biomass, likely due to a biologically mediated positive feedback under high nutrient conditions. Solutions toward managing harmful cyanobacteria should thus consider lake morphometric characteristics and emphasize nutrient control, independently of temperature gradients, since local factors are more critical - and more amenable to controls - than global external forces.

Predicting cyanobacterial biovolume from water temperature and conductivity using a Bayesian compound Poisson-Gamma model.

Eutrophication and climate change scenarios engender the need to develop good predictive models for harmful cyanobacterial blooms (CyanoHABs). Nevertheless, modeling cyanobacterial biomass is a challenging task due to strongly skewed distributions that include many absences as well as extreme values (dense blooms). Most modeling approaches alter the natural distribution of the data by splitting them into zeros (absences) and positive values, assuming that different processes underlie these two components. Our objectives were (1) to develop a probabilistic model relating cyanobacterial biovolume to environmental variables in the Río de la Plata Estuary (35°S, 56°W, n = 205 observations) considering all biovolume values (zeros and positive biomass) as part of the same process; and (2) to use the model to predict cyanobacterial biovolume under different risk level scenarios using water temperature and conductivity as explanatory variables. We developed a compound Poisson-Gamma (CPG) regression model, an approach that has not previously been used for modeling phytoplankton biovolume, within a Bayesian hierarchical framework. Posterior predictive checks showed that the fitted model had a good overall fit to the observed cyanobacterial biovolume and to more specific features of the data, such as the proportion of samples crossing three threshold risk levels (0.2, 1 and 2 mm³ L-1) at different water temperatures and conductivities. The CPG model highlights the strong control of cyanobacterial biovolume by nonlinear and interactive effects of water temperature and conductivity. The highest probability of crossing the three biovolume levels occurred at 22.2 °C and at the lowest observed conductivity (∼0.1 mS cm-1). Cross-validation of the fitted model using out-of-sample observations (n = 72) showed the model's potential to be used in situ, as it enabled prediction of cyanobacterial biomass based on two readily measured variables (temperature and conductivity), making it an interesting tool for early alert systems and management strategies. Furthermore, this novel application demonstrates the potential of the Bayesian CPG approach for predicting cyanobacterial dynamics in response to environmental change.

Temperature and precipitation shape the distribution of harmful cyanobacteria in subtropical lotic and lentic ecosystems.

Cyanobacterial blooms are expected to become more frequent in freshwaters globally due to eutrophication and climate change effects. However, our knowledge about cyanobacterial biogeography in the subtropics, particularly in lotic ecosystems, is still very limited and the relationship of blooms to temperature and precipitation remains unclear. We took advantage of a comprehensive database of field data compiled over several years (1997 to 2015) to compare cyanobacteria biomass and distribution between lentic and lotic subtropical freshwaters (36 ecosystems, 30°-35°S) and to investigate the role of water temperature and precipitation as significant predictors in eutrophic ecosystems. A filamentous Nostocales, Dolichospermum (Anabaena), was the most widely distributed and frequent genus in the region of the study, followed by the colonial Microcystis, supporting observations of a global latitudinal pattern. Similar total cyanobacteria biovolumes (TCB) were found in lentic and lotic ecosystems, but the proportion of Dolichospermum was higher in lotic ecosystems. Using generalized linear models (GLMs), we found that temperature and rainfall explained 27% of the variation in TCB in lotic ecosystems, while temperature explained 19 and 28% of Dolichospermum and Microcystis biovolume, respectively. In lentic ecosystems, accumulated rainfall explained 34% of the variation of Microcystis biovolume while temperature explained 64%. Our results imply that the increase in extreme meteorological events and temperature predicted by climate models will promote increasingly severe cyanobacterial blooms in eutrophic subtropical freshwaters. Our analysis provides new information about the occurrence of bloom-forming cyanobacteria for southeastern South America and thus fills an important knowledge gap for subtropical freshwaters.