Predictive value of protozoan assemblages for assessing water quality in subtropical urban ponds

Abstract

Protozoans are globally distributed across aquatic environments and play key roles in ecosystem functioning. This study assessed how environmental filters associated with urbanization shape the spatial and temporal variation of protozoan assemblages in shallow urban lakes and evaluated their predictive capacity for trophic status and water quality assessment. Four urban ponds located in Santa Fe and Santo Tomé cities (Argentina) were sampled over one year. Several environmental relevant variables were measured, including inorganic nutrient concentrations and indicators of organic matter contamination. With Generalized Linear Models and partial Canonical Correspondence Analysis, we first focused on total protozoan density and evaluated the influence of the environment, time, and spatial predictors on the distribution of the most abundant groups. Multiple regression models and Principal Coordinates Analysis (PCoA) were applied to estimate the bioindicator value of dominant protozoans’ groups. Protozoans showed significantly higher total densities during warmer months and differed among ponds. Eight of sixteen recorded groups were dominant and displayed non-uniform distributions. Nutrient availability, temperature, pH, and organic matter contamination were identified as key predictors of the assemblage’s structure. Moreover, multiple regression models indicated that at least four groups (Choreotrichia, Haptoria, Arcellinida and Hypotrichia) responded significantly to eutrophication, organic contamination, and pH variation. Overall, protozoan assemblages responded to environmental, spatial, and temporal drivers. These results suggest that taxonomic levels such as class or family can function as sensitive and operational indicators of water quality in urban ponds, particularly in monitoring programs requiring rapid, cost-effective, and feasible assessment tools.