Abstract
Predictive models for chlorophyll-a concentration are the most common ecological tools for water-quality management. However, the interactions among factors driving eutrophication processes remain poorly understood. In addition to nutrient concentrations, other variables such as, for instance, hydrology, land use and biotic interactions may also be included as explanatory variables. Here, we compared a set of a priori models (which included local, morphological, and landscape variables) with respect to their power to predict chlorophyll-a concentration in 21 reservoirs of central Brazil. The best model, selected according to the Akaike information criterion, explained 67.7% of the variation in chlorophyll-a concentration, and indicated a positive relationship with total phosphorus concentration (the main predictor in our model) and depth. Turbidity was negatively correlated with chlorophyll-a concentration. Contrary to recent studies indicating the importance of landscape predictors, our results suggested a preponderance of local factors in determining chlorophyll-a concentration, and that the control of phosphorus sources in tropical reservoirs is as important as it is in temperate ecosystems. We also detected a substantial uncertainty regarding the best model, suggesting that further studies should focus on explicitly modeling the variation in the strength of the relationships between chlorophyll-a and explanatory variables.
Published Version
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