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Abstract Whole lake residence time has been associated with various water quality parameters, including harmful algal blooms. Despite observations of spatial variability in commonly measured lake water quality parameters, little attention is given to the spatial variability of residence time in lakes. In this paper we use water age as a surrogate for residence time and we examine its spatial and temporal distribution in 10 bays of varying size in Lake George, New York (USA). Using a validated hydrodynamic model against observations of water temperature and water currents, and using simulated water age, we show that the average residence time in most of the bays is less than 3 days. Timeseries of bay‐average water age shows that it can sharply decrease within 1 day due to a strong wind event. The average spatial distribution is shown to be non‐uniform, with only a small section of the bottom layer of the bays having a substantially greater age, which may be more than 1 week in certain bays. Snapshots of water age transects indicate that strong wind events substantially change the vertical distribution of water age in some bays, even to the extent of inverting the distribution. The substantial decreases of water age in the bays were associated with the shallowing and deepening of the thermocline. Our results highlight how variations in water residence times within lakes could introduce substantial variation in water quality attributes. Whole lake residence times may serve as a poor proxy to understand the dynamics of water masses, especially in large and morphologically complex waterbodies. 

Abstract Identifying the scaling rules describing ecological patterns across time and space is a central challenge in ecology. Taylor's law of fluctuation scaling, which states that the variance of a population's size or density is proportional to a positive power of the mean size or density, has been widely observed in population dynamics and characterizes variability in multiple scientific domains. However, it is unclear if this phenomenon accurately describes ecological patterns across many orders of magnitude in time, and therefore links otherwise disparate observations. Here, we use water clarity observations from 10,531 days of high‐frequency measurements in 35 globally distributed lakes, and lower‐frequency measurements over multiple decades from 6342 lakes to test this unknown. We focus on water clarity as an integrative ecological characteristic that responds to both biotic and abiotic drivers. We provide the first documentation that variations in ecological measurements across diverse sites and temporal scales exhibit variance patterns consistent with Taylor's law, and that model coefficients increase in a predictable yet non‐linear manner with decreasing observation frequency. This discovery effectively links high‐frequency sensor network observations with long‐term historical monitoring records, thereby affording new opportunities to understand and predict ecological dynamics on time scales from days to decades.