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Understanding controls on primary productivity is essential for describing ecosystems and their responses to environmental change. Lake primary production is strongly controlled by inputs of nutrients and colored dissolved organic matter. While past studies have developed mathematical models of this nutrient-color paradigm, broad empirical tests of these models are scarce. We compiled data from 58 diverse and globally distributed and mostly temperate lakes to test such a model and improve understanding and prediction of the controls on lake primary production. These lakes varied widely in size (0.02-2300 km2), pelagic gross primary production (20-8000 mg C m-2 d-1), and other characteristics. The data package includes high-frequency dissolved oxygen, water temperature, wind speed, and solar radiation data as well as daily estimates of GPP and ER derived from those data. In addition, the data package includes median in-lake and stream concentrations of dissolved organic carbon and total phosphorus for a subset of 18 of those lakes. 

Abstract Chlorophyll and total phosphorus (TP) concentrations are key indicators of lake water quality and the relationship between them is a common tool for assessing lake trophic status. Despite the application of the chlorophyll–TP relationship in management settings, there is still an absence of a mechanistic understanding underlying its shape. We leveraged a process‐based model that focuses primarily on biogeochemical and physiological mechanisms to develop a framework that reconciles interactions between multiscale drivers of the chlorophyll–TP relationship, such as hydrologic P loads, lake shape, and algal physiology. We found that combinations of lake shape and hydrologic P load induce broad shifts in algal limitation status that underly the shape of the chlorophyll–TP relationship. Furthermore, we highlight the importance of algal traits in controlling shifts in limitation. Our framework ties key landscape and ecosystem features to biological limitation and provides a synthetic and process‐based understanding of the chlorophyll–TP relationship. 

Abstract The limits on primary production vary in complex ways across space and time. Strong tests of clear conceptual models have been instrumental in understanding these patterns in both terrestrial and aquatic ecosystems. Here we present the first experimental test of a new model describing how shifts from nutrient to light limitation control primary productivity in lake ecosystems as hydrological inputs of nutrients and organic matter vary. We found support for two key predictions of the model: that gross primary production (GPP) follows a hump‐shaped relationship with increasing dissolved organic carbon (DOC) concentrations; and that the maximum GPP, and the critical DOC concentration at which the hump occurs, are determined by the stoichiometry and chromophoricity of the hydrological inputs. Our results advance fundamental understanding of the limits on aquatic primary production, and have important applications given ongoing anthropogenic alterations of the nutrient and organic matter inputs to surface waters. 

Abstract Understanding controls on primary productivity is essential for describing ecosystems and their responses to environmental change. In lakes, pelagic gross primary productivity (GPP) is strongly controlled by inputs of nutrients and dissolved organic matter. Although past studies have developed process models of this nutrient‐color paradigm (NCP), broad empirical tests of these models are scarce. We used data from 58 globally distributed, mostly temperate lakes to test such a model and improve understanding and prediction of the controls on lake primary production. The model includes three state variables–dissolved phosphorus, terrestrial dissolved organic carbon (DOC), and phytoplankton biomass–and generates realistic predictions for equilibrium rates of pelagic GPP. We calibrated our model using a Bayesian data assimilation technique on a subset of lakes where DOC and total phosphorus (TP) loads were known. We then asked how well the calibrated model performed with a larger set of lakes. Revised parameter estimates from the updated model aligned well with existing literature values. Observed GPP varied nonlinearly with both inflow DOC and TP concentrations in a manner consistent with increasing light limitation as DOC inputs increased and decreasing nutrient limitation as TP inputs increased. Furthermore, across these diverse lake ecosystems, model predictions of GPP were highly correlated with observed values derived from high‐frequency sensor data. The GPP predictions using the updated parameters improved upon previous estimates, expanding the utility of a process model with simplified assumptions for water column mixing. Our analysis provides a model structure that may be broadly useful for understanding current and future patterns in lake primary production.