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.

In lakes, the production and emission of methane (CH 4) have been linked to lake trophic status. However, few studies have quantified the temporal response of lake CH 4 dynamics to primary productivity at the ecosystem scale or considered how the response may vary across lakes. Here, we investigate relationships between lake CH 4 dynamics and ecosystem primary productivity across both space and time using data from five lakes in northern Wisconsin, USA. From 2014 to 2019, we estimated hypolimnetic CH 4 storage rates for each lake using timeseries of hypolimnetic CH 4 concentration through the summer season. Across all lakes and years, hypolimnetic CH 4 storage ranged from <0.001 to 7.6 mmol CH 4 m −2 d −1 and was positively related to the mean summer rate of gross primary productivity (GPP). However, within-lake temporal responses to GPP diverged from the spatial relationship, and GPP was not a significant predictor of interannual variability in CH 4 storage at the lake scale. Using these data, we consider how and why temporal responses may differ from spatial patterns and demonstrate how extrapolating cross-lake relationships for prediction at the lake scale may substantially overestimate the rate of change of CH 4 dynamics in response to lake primary productivity. We conclude that future predictions of lake-mediated climate feedbacks in response to a shifting distribution of trophic status should incorporate both varying lake responses and the temporal scale of change. Plain Language Summary Many lakes produce substantial amounts of methane, a potent greenhouse gas. Previous research has found that more methane is produced from lakes with high algal biomass. However, little is known about how methane dynamics from a single lake respond to annual changes in algal biomass. By examining lake methane dynamics and metrics of algal biomass from five lakes across 5 years, we find that within-lake responses of methane dynamics do not align with the across-lake patterns we see when comparing different lakes. Within-lake methane responses were different between lakes and were undetectable in some lakes. Understanding the temporal scale of how lakes respond to changes in algal biomas is important for predicting the role of lakes for producing methane under future environmental change scenarios.

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Understanding controls of lake primary productivity is imperative to tackling issues related to water quality. A common way to assess lake water quality across broad spatial scales is the relationship between chlorophyll concentration and total phosphorus (TP). However, despite continuous refinement in our understanding of the chlorophyll-TP relationship, there is still uncertainty regarding the mechanisms underpinning the variation in chlorophyll at a given TP concentration. We used a process-model that primarily focuses on biogeochemical and physiological mechanisms to infer broad shifts in algal limitation status underly the shape of the chlorophyll-TP relationship and these shifts in limitation are a product of interactions among landscape, ecosystem, and algal physiologic drivers. Our work provides integrative insights that place patterns of lake primary productivity in a more general framework.