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Abstract Local and regional‐scaled studies point to the important role of lake type (natural lakes vs. reservoirs), surface water connectivity, and ecological context (multi‐scaled natural settings and human factors) in mediating lake responses to disturbances like drought. However, we lack an understanding at the macroscale that incorporates multiple scales (lake, watershed, region) and a variety of ecological contexts. Therefore, we used data from the LAGOS‐US research platform and applied a local water year timeframe to 62,927 US natural lakes and reservoirs across 17 ecoregions to examine how chlorophyllaresponds to drought across various ecological contexts. We evaluated chlorophyllachanges relative to each lake's baseline and drought year. Drought led to lower and higher chlorophyllain 18% and 20%, respectively, of lakes (both natural lakes and reservoirs included). Natural lakes had higher magnitudes of change and probabilities of increasing chlorophylladuring droughts than reservoirs, and these differences were particularly pronounced in isolated and highly‐connected lakes. Drought responses were also related to long‐term average lake chlorophyllain complex ways, with a positive correlation in less productive lakes and a negative correlation in more productive lakes, and more pronounced drought responses in higher‐productivity lakes than lower‐productivity lakes. Thus, lake chlorophyll responses to drought are related to interactions between lake type and surface connectivity, long‐term average chlorophylla, and many other multi‐scaled ecological factors (e.g., soil erodibility, minimum air temperature). These results reinforce the importance of integrating multi‐scaled ecological context to determine and predict the impacts of global changes on lakes. 

Climate change is predicted to intensify lake algal blooms globally and result in regime shifts. However, observed increases in algal biomass do not consistently correlate with air temperature or precipitation, and evidence is lacking for a causal effect of climate or the nonlinear dynamics needed to demonstrate regime shifts. We modeled the causal effects of climate on annual lake chlorophyll (a measure of algal biomass) over 34 y for 24,452 lakes across broad ecoclimatic zones of the United States and evaluated the potential for regime shifts. We found that algal biomass was causally related to climate in 34% of lakes. In these cases, 71% exhibited abrupt but mostly temporary shifts as opposed to persistent changes, 13% had the potential for regime shifts. Climate was causally related to algal biomass in lakes experiencing all levels of human disturbance, but with different likelihood. Climate causality was most likely to be observed in lakes with minimal human disturbance and cooler summer temperatures that have increased over the 34 y studied. Climate causality was variable in lakes with low to moderate human disturbance, and least likely in lakes with high human disturbance, which may mask climate causality. Our results explain some of the previously observed heterogeneous climate responses of lake algal biomass globally and they can be used to predict future climate effects on lakes. 

Local‐scale environmental justice studies of freshwaters have found that marginalized populations are more likely than others to be burdened with poor‐quality waters. However, studies have yet to examine whether monitoring data are sufficient to determine the generality of such results at the national scale. We analyzed racial and ethnic community composition surrounding lakes and the presence of one‐time and long‐term (≥15 years) water‐quality data across the conterminous US. Relative to lakes in White and non‐Hispanic communities, lakes in communities of color and Hispanic communities were three times less likely to be monitored at least once. Moreover, as compared to lakes in White communities, lakes in communities of color were seven times less likely to have long‐term monitoring data; similarly, as compared to lakes in non‐Hispanic communities, lakes in Hispanic communities were nineteen times less likely to have long‐term monitoring data. Given this evidence, assessing the current water quality of and temporal changes in lakes in communities of color and Hispanic communities is extremely difficult. To achieve equitable management outcomes for people of all racial and ethnic backgrounds, freshwater monitoring programs must expand their sampling and revise their designs. 

Abstract A variety of classification approaches are used to facilitate understanding, prediction, monitoring, and the management of lakes. However, broad‐scale applicability of current approaches is limited by either the need for in situ lake data, incompatibilities among approaches, or a lack of empirical testing of approaches based on ex situ data. We developed a new geographic classification approach for 476,697 lakes ≥ 1 ha in the conterminous U.S. based on lake archetypes representing end members along gradients of multiple geographic features. We identified seven lake archetypes with distinct combinations of climate, hydrologic, geologic, topographic, and morphometric properties. Individual lakes were assigned weights for each of the seven archetypes such that groups of lakes with similar combinations of archetype weights tended to cluster spatially (although not strictly contiguous) and to have similar limnological properties (e.g., concentrations of nutrients, chlorophylla(Chla), and dissolved organic carbon). Further, archetype lake classification improved commonly measured limnological relationships (e.g., between nutrients and Chla) compared to a global model; a discrete archetype classification slightly outperformed an ecoregion classification; and considering lakes as continuous mixtures of archetypes in a more complex model further improved fit. Overall, archetype classification of US lakes as continuous mixtures of geographic features improved understanding and prediction of lake responses to limnological drivers and should help researchers and managers better characterize and forecast lake states and responses to environmental change. 

The LAGOS-US LIMNO data package is one of the core data modules of LAGOS-US, an extensible research-ready platform designed to study the 479,950 lakes and reservoirs larger than or equal to 1 ha in the conterminous US (48 states plus the District of Columbia). The LIMNO module contains in situ observations of 47 parameters of lake physics, chemistry, and biology (hereafter referred to as chemistry) from lake surface samples (defined as observations taken from the epilimnion of a lake) obtained from the Water Quality Portal, the National Lakes Assessment (2007, 2012, 2017), and NEON programs. LIMNO provides 3,511,020 observations across all parameters collected between 1975 and 2021 from 20,329 lakes; the number of observations per lake ranged from 1 to 20,605 with a median of 32. The database design that supports the LAGOS-US research platform was created based on several important design features: lakes are the fundamental unit of consideration, all lakes in the spatial extent above the minimum size must be represented, and most information is connected to individual lakes. The design is modular, interoperable (the modules can be used with each other, as well as other comprehensive lake data products such as the USGS NHD), and extensible (future database modules can be developed and used in the LAGOS-US research platform by others). Users are encouraged to use the other two core data modules that are part of the LAGOS-US platform: LOCUS (location, identifiers, and physical characteristics of lakes and their watersheds) and GEO (characteristics defining geospatial and temporal ecological setting quantified at multiple spatial divisions) that are each found in their own data packages.