Stoichiometric imbalances complicate prediction of phytoplankton biomass in U.S. lakes: Implications for nutrient criteria

다국어 초록 (Multilingual Abstract)

Using National Lakes Assessment data, we evaluated the influence of total N (TN), total P (TP), and other variables on lake chlorophyll‐a concentrations. With simple linear regressions, high TN/TP samples biased predictions based on TN, and low TN/TP samples biased predictions based on TP. The bias problem was corrected, and correlation was improved, by splitting the dataset at the TN/TP ratio we estimated to be indicative of a balanced supply and developing separate regressions that predict chlorophyll‐a based on TP, TN, dissolved inorganic N (DIN), dissolved organic carbon (DOC), nonalgal light attenuation, depth, area, latitude, elevation, and conductivity. Both nutrients were excellent predictors, and nonalgal light attenuation was the next most influential predictor. The regression analysis suggested that a potential for P only limitation (high TN/TP, 17% of samples) or N only limitation (low TN/TP, 14% of samples) can be inferred at the extremes of the TN/TP range. However, 69% of samples had an intermediate TN/TP ratio where it is difficult to infer anything about potential nutrient limitations (biomass could be N limited, P limited, N and P co‐limited, or not limited by nutrients at all). Our results show that when developing phytoplankton response relationships using cross‐lake datasets that span a wide range of trophic states, it is important to consider whether and how biomass is influenced by confounding factors—such as differences in the relative supply of N and P—so that biomass is not underestimated or overestimated, and nutrient criteria are not under‐protective or over‐protective.