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Lake trophic state is a key ecosystem property that integrates a lake’s physical, chemical, and biological processes. Despite the importance of trophic state as a gauge of lake water quality, standardized and machine-readable observations are uncommon. Remote sensing presents an opportunity to detect and analyze lake trophic state with reproducible, robust methods across time and space. We used Landsat surface reflectance data to create the first compendium of annual lake trophic state for 55,662 lakes of at least 10 ha in area throughout the contiguous United States from 1984 through 2020. The dataset was constructed with FAIR data principles (Findable, Accessible, Interoperable, and Reproducible) in mind, where data are publicly available, relational keys from parent datasets are retained, and all data wrangling and modeling routines are scripted for future reuse. Together, this resource offers critical data to address basic and applied research questions about lake water quality at a suite of spatial and temporal scales.

 

Rapid changes in climate and land use are having substantial and interacting impacts on lake water quality around the world. Here, we synthesized time-series data for dissolved oxygen, temperature, chlorophyll-a, total phosphorus, total nitrogen, and dissolved organic carbon at multiple depths in 822 lakes to facilitate analyses of these changes. The dataset extends from 1921–2022, with a median data duration of 29 years (range 5-102) and a median of 5 unique sampling dates per year at each lake. Lakes in the dataset have a median depth of 12.5 m (range 1.5–480 m), median surface area of 85.4 ha (range: 0.5–237000 ha) and median elevation of 264 m (range: -215–2804). The lakes are located in 18 countries across 5 continents, with latitudes ranging from -42.6 to 68.3. To facilitate interoperability with other large-scale datasets, each lake is linked to a unique hydroLAKES lake ID when possible (n = 683). 

Reductions in ice cover duration and earlier ice breakup are two of the most prevalent responses to climate warming in lakes in recent decades. In dimictic lakes, the subsequent periods of spring mixing and summer stratification are both likely to change in response to these phenological changes in ice cover. Here, we used a modeling approach to simulate the effect of changes in latitude on long‐term trends in duration of ice cover, spring mixing, and summer stratification by “moving” a well‐studied lake across a range of latitudes in North America (35.2°N to 65.7°N). We found a changepoint relationship between the timing of ice breakup vs. spring mixing duration on 09 May. When ice breakup occurred before 09 May, which routinely occurred at latitudes < 47°N, spring mixing was longer and more variable; when ice breakup occurred after 09 May at latitudes > 47°N, spring mixing averaged 1 day with low variability. In contrast, the duration of summer stratification showed a relatively slower rate of increase when ice breakup occurred before 09 May (< 47°N) compared to a 109% faster rate of increase when ice breakup was after 09 May (> 47°N). Projected earlier ice breakup can result in important nonlinear changes in the relative duration of spring mixing and summer stratification, which can lead to mixing regime shifts that influence the severity of oxygen depletion differentially across latitudes.

 

We present and evaluate an update to the process‐based lake model MyLake that includes a time‐varying linkage between light attenuation of both photosynthetically active radiation (PAR) and ultraviolet (UV) radiation wavelengths to changes in dissolved organic carbon (DOC). In many parts of northeastern North America and Europe, DOC in lakes has rapidly increased, leading to reduced water transparency and increases in light attenuation. These changes alter the vertical light and heat distribution that affect vertical structuring of temperature and dissolved oxygen. We use this model update to test the responsiveness of PAR and UV attenuation to short‐term fluctuations in DOC and with a test case of long‐term browning at Lake Giles (Pennsylvania). Lake Giles has browned significantly since the late 1980s, and three decades of detailed empirical data have indicated more than a doubling of DOC concentrations, and consequent increases in PAR and UV attenuation, warming surface waters, cooling deep waters, and increasing deepwater oxygen depletion. We found that the model performance improved by 16% and 52% for long‐term trends in PAR and UV attenuation, respectively, when these coefficients respond directly to in‐lake DOC concentrations. Further, long‐term trends in surface water warming, deepwater cooling, and deepwater oxygen depletion in Lake Giles were better captured by the model following this update, and were very rapid due to its high water transparency and low DOC. Hence, incorporating a responsive link between DOC and light attenuation in lake models is key to understanding long‐term lake browning patterns, mechanisms, and ecological consequences.

 

Declining oxygen concentrations in the deep waters of lakes worldwide pose a pressing environmental and societal challenge. Existing theory suggests that low deep‐water dissolved oxygen (DO) concentrations could trigger a positive feedback through which anoxia (i.e., very low DO) during a given summer begets increasingly severe occurrences of anoxia in following summers. Specifically, anoxic conditions can promote nutrient release from sediments, thereby stimulating phytoplankton growth, and subsequent phytoplankton decomposition can fuel heterotrophic respiration, resulting in increased spatial extent and duration of anoxia. However, while the individual relationships in this feedback are well established, to our knowledge, there has not been a systematic analysis within or across lakes that simultaneously demonstrates all of the mechanisms necessary to produce a positive feedback that reinforces anoxia. Here, we compiled data from 656 widespread temperate lakes and reservoirs to analyze the proposed anoxia begets anoxia feedback. Lakes in the dataset span a broad range of surface area (1–126,909 ha), maximum depth (6–370 m), and morphometry, with a median time‐series duration of 30 years at each lake. Using linear mixed models, we found support for each of the positive feedback relationships between anoxia, phosphorus concentrations, chlorophyllaconcentrations, and oxygen demand across the 656‐lake dataset. Likewise, we found further support for these relationships by analyzing time‐series data from individual lakes. Our results indicate that the strength of these feedback relationships may vary with lake‐specific characteristics: For example, we found that surface phosphorus concentrations were more positively associated with chlorophyllain high‐phosphorus lakes, and oxygen demand had a stronger influence on the extent of anoxia in deep lakes. Taken together, these results support the existence of a positive feedback that could magnify the effects of climate change and other anthropogenic pressures driving the development of anoxia in lakes around the world.