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Temporal Secchi depth trends are used in lake assessment to evaluate lake condition and possible shifts in trophic state. For accurate lake assessments, it is important to differentiate regional trends from lake‐specific trends, but this can be confounded by interacting factors. We present a divergent trend analysis which uses temporal patterns of Secchi depth water clarity from 1999 to 2018 for five different types of reference lakes from minimally disturbed watersheds to create dynamic baselines against which we evaluate Secchi depth trends from nonreference lakes in Maine, USA. We used mixed‐effect generalized additive models to generate smoothed curves of the expected baseline Secchi depth for each reference lake type to account for the nonlinear dynamics of lake condition through time. The majority of nonreference lakes (74%) showed no difference between measured trend (actual Secchi depth data) and divergent trend (residual Secchi depth from baseline trends). The most common difference in lakes with inconsistent trend test results showed stability in measured trends but apparent declining trends in divergent Secchi depth clarity. We used a Dynamic Factor Analysis (DFA) model to help interpret the variation and shifts observed in baseline reference lake trends. The best DFA model identified two common trends in water clarity among lake types and precipitation during the primary stratification season as the most informative covariable. Because precipitation amount and intensity are expected to increase according to predictive climate models for the Northeast US, our results suggest that baseline lake clarity in Maine will decrease with climate change.

Lakes process both terrestrial and aquatic organic matter, and the relative contribution from each source is often measured via ecosystem metabolism and terrestrial resource use in the food web (i.e., consumer allochthony). Yet, ecosystem metabolism and consumer allochthony are rarely considered together, despite possible interactions and potential for them to respond to the same lake characteristics. In this study, we compiled global datasets of lake gross primary production (GPP), ecosystem respiration (ER), and zooplankton allochthony to compare the strength and shape of relationships with physicochemical characteristics across a broad set of lakes. GPP was positively related to total phosphorus (TP) in lakes with intermediate TP concentrations (11–75 μg L⁻¹) and was highest in lakes with intermediate dissolved organic carbon (DOC) concentrations. While ER and GPP were strongly positively correlated, decoupling occurred at high DOC concentrations. Lastly, allochthony had a unimodal relationship with TP and related variably to DOC. By integrating metabolism and allochthony, we identified similar change points in GPP and zooplankton allochthony at intermediate DOC (4.5–10 mg L⁻¹) and TP (8–20 μg L⁻¹) concentrations, indicating that allochthony and GPP may be coupled and inversely related. The ratio of DOC:nutrients also helped to identify conditions where lake organic matter processing responded more to autochthonous or allochthonous organic matter sources. As lakes globally face eutrophication and browning, predicting how lake organic matter processing will respond requires an updated paradigm that incorporates nonlinear dynamics and interactions.