National-scale remotely sensed lake trophic state from 1984 through 2020.

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.

Freshwater salinisation: a research agenda for a saltier world.

The widespread salinisation of freshwater ecosystems poses a major threat to the biodiversity, functioning, and services that they provide. Human activities promote freshwater salinisation through multiple drivers (e.g., agriculture, resource extraction, urbanisation) that are amplified by climate change. Due to its complexity, we are still far from fully understanding the ecological and evolutionary consequences of freshwater salinisation. Here, we assess current research gaps and present a research agenda to guide future studies. We identified different gaps in taxonomic groups, levels of biological organisation, and geographic regions. We suggest focusing on global- and landscape-scale processes, functional approaches, genetic and molecular levels, and eco-evolutionary dynamics as key future avenues to predict the consequences of freshwater salinisation for ecosystems and human societies.

Shifting Patterns of Summer Lake Color Phenology in Over 26,000 US Lakes.

Lakes are often defined by seasonal cycles. The seasonal timing, or phenology, of many lake processes are changing in response to human activities. However, long-term records exist for few lakes, and extrapolating patterns observed in these lakes to entire landscapes is exceedingly difficult using the limited number of available in situ observations. Limited landscape-level observations mean we do not know how common shifts in lake phenology are at macroscales. Here, we use a new remote sensing data set, LimnoSat-US, to analyze U.S. summer lake color phenology between 1984 and 2020 across more than 26,000 lakes. Our results show that summer lake color seasonality can be generalized into five distinct phenology groups that follow well-known patterns of phytoplankton succession. The frequency with which lakes transition from one phenology group to another is tied to lake and landscape level characteristics. Lakes with high inflows and low variation in their seasonal surface area are generally more stable, while lakes in areas with high interannual variations in climate and catchment population density show less stability. Our results reveal previously unexamined spatiotemporal patterns in lake seasonality and demonstrate the utility of LimnoSat-US, which, with over 22 million remote sensing observations of lakes, creates novel opportunities to examine changing lake ecosystems at a national scale.

Lakes at Risk of Chloride Contamination.

Lakes in the Midwest and Northeast United States are at risk of anthropogenic chloride contamination, but there is little knowledge of the prevalence and spatial distribution of freshwater salinization. Here, we use a quantile regression forest (QRF) to leverage information from 2773 lakes to predict the chloride concentration of all 49 432 lakes greater than 4 ha in a 17-state area. The QRF incorporated 22 predictor variables, which included lake morphometry characteristics, watershed land use, and distance to the nearest road and interstate. Model predictions had an r2 of 0.94 for all chloride observations, and an r2 of 0.86 for predictions of the median chloride concentration observed at each lake. The four predictors with the largest influence on lake chloride concentrations were low and medium intensity development in the watershed, crop density in the watershed, and distance to the nearest interstate. Almost 2000 lakes are predicted to have chloride concentrations above 50 mg L-1 and should be monitored. We encourage management and governing agencies to use lake-specific model predictions to assess salt contamination risk as well as to augment their monitoring strategies to more comprehensively protect freshwater ecosystems from salinization.

A lake classification concept for a more accurate global estimate of the dissolved inorganic carbon export from terrestrial ecosystems to inland waters.

The magnitude of lateral dissolved inorganic carbon (DIC) export from terrestrial ecosystems to inland waters strongly influences the estimate of the global terrestrial carbon dioxide (CO2) sink. At present, no reliable number of this export is available, and the few studies estimating the lateral DIC export assume that all lakes on Earth function similarly. However, lakes can function along a continuum from passive carbon transporters (passive open channels) to highly active carbon transformers with efficient in-lake CO2 production and loss. We developed and applied a conceptual model to demonstrate how the assumed function of lakes in carbon cycling can affect calculations of the global lateral DIC export from terrestrial ecosystems to inland waters. Using global data on in-lake CO2 production by mineralization as well as CO2 loss by emission, primary production, and carbonate precipitation in lakes, we estimated that the global lateral DIC export can lie within the range of [Formula: see text] to [Formula: see text] Pg C yr-1 depending on the assumed function of lakes. Thus, the considered lake function has a large effect on the calculated lateral DIC export from terrestrial ecosystems to inland waters. We conclude that more robust estimates of CO2 sinks and sources will require the classification of lakes into their predominant function. This functional lake classification concept becomes particularly important for the estimation of future CO2 sinks and sources, since in-lake carbon transformation is predicted to be altered with climate change.

Long-term chloride concentrations in North American and European freshwater lakes.

Anthropogenic sources of chloride in a lake catchment, including road salt, fertilizer, and wastewater, can elevate the chloride concentration in freshwater lakes above background levels. Rising chloride concentrations can impact lake ecology and ecosystem services such as fisheries and the use of lakes as drinking water sources. To analyze the spatial extent and magnitude of increasing chloride concentrations in freshwater lakes, we amassed a database of 529 lakes in Europe and North America that had greater than or equal to ten years of chloride data. For each lake, we calculated climate statistics of mean annual total precipitation and mean monthly air temperatures from gridded global datasets. We also quantified land cover metrics, including road density and impervious surface, in buffer zones of 100 to 1,500 m surrounding the perimeter of each lake. This database represents the largest global collection of lake chloride data. We hope that long-term water quality measurements in areas outside Europe and North America can be added to the database as they become available in the future.

Salting our freshwater lakes.

The highest densities of lakes on Earth are in north temperate ecosystems, where increasing urbanization and associated chloride runoff can salinize freshwaters and threaten lake water quality and the many ecosystem services lakes provide. However, the extent to which lake salinity may be changing at broad spatial scales remains unknown, leading us to first identify spatial patterns and then investigate the drivers of these patterns. Significant decadal trends in lake salinization were identified using a dataset of long-term chloride concentrations from 371 North American lakes. Landscape and climate metrics calculated for each site demonstrated that impervious land cover was a strong predictor of chloride trends in Northeast and Midwest North American lakes. As little as 1% impervious land cover surrounding a lake increased the likelihood of long-term salinization. Considering that 27% of large lakes in the United States have >1% impervious land cover around their perimeters, the potential for steady and long-term salinization of these aquatic systems is high. This study predicts that many lakes will exceed the aquatic life threshold criterion for chronic chloride exposure (230 mg L-1), stipulated by the US Environmental Protection Agency (EPA), in the next 50 y if current trends continue.

The importance of lake-specific characteristics for water quality across the continental United States.

Lake water quality is affected by local and regional drivers, including lake physical characteristics, hydrology, landscape position, land cover, land use, geology, and climate. Here, we demonstrate the utility of hypothesis testing within the landscape limnology framework using a random forest algorithm on a national-scale, spatially explicit data set, the United States Environmental Protection Agency's 2007 National Lakes Assessment. For 1026 lakes, we tested the relative importance of water quality drivers across spatial scales, the importance of hydrologic connectivity in mediating water quality drivers, and how the importance of both spatial scale and connectivity differ across response variables for five important in-lake water quality metrics (total phosphorus, total nitrogen, dissolved organic carbon, turbidity, and conductivity). By modeling the effect of water quality predictors at different spatial scales, we found that lake-specific characteristics (e.g., depth, sediment area-to-volume ratio) were important for explaining water quality (54-60% variance explained), and that regionalization schemes were much less effective than lake specific metrics (28-39% variance explained). Basin-scale land use and land cover explained between 45-62% of variance, and forest cover and agricultural land uses were among the most important basin-scale predictors. Water quality drivers did not operate independently; in some cases, hydrologic connectivity (the presence of upstream surface water features) mediated the effect of regional-scale drivers. For example, for water quality in lakes with upstream lakes, regional classification schemes were much less effective predictors than lake-specific variables, in contrast to lakes with no upstream lakes or with no surface inflows. At the scale of the continental United States, conductivity was explained by drivers operating at larger spatial scales than for other water quality responses. The current regulatory practice of using regionalization schemes to guide water quality criteria could be improved by consideration of lake-specific characteristics, which were the most important predictors of water quality at the scale of the continental United States. The spatial extent and high quality of contextual data available for this analysis makes this work an unprecedented application of landscape limnology theory to water quality data. Further, the demonstrated importance of lake morphology over other controls on water quality is relevant to both aquatic scientists and managers.