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.

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.

Chemistry of surface water, precipitation, throughfall, leaves, sediment, soil, and air near a gold mining region in Peru.

Artisanal and small-scale gold mining (ASGM) is the primary global source of anthropogenic mercury (Hg) emissions and a large source of landscape change. ASGM occurs throughout the world, including in the Peruvian Amazon. This data set contains measurements of surface water, precipitation, throughfall, leaves, sediment, soil, and air samples from across the Madre de Dios region of Peru, in locations near and remote from ASGM. These data were collected to determine the fate and transport of Hg across the landscape. Samples were collected in 2018 and 2019. Data predominantly included total Hg and methyl Hg concentrations in surface water, precipitation, throughfall, leaves, sediment, soil, and air. Additional water and soil parameters were also measured to better characterize their chemistry. There are no copyright restrictions; please cite this data paper when the data are used in publication.

Artificial lake expansion amplifies mercury pollution from gold mining.

Artisanal and small-scale gold mining (ASGM) is the largest global source of anthropogenic mercury emissions. However, little is known about how effectively mercury released from ASGM is converted into the bioavailable form of methylmercury in ASGM-altered landscapes. Through examination of ASGM-impacted river basins in Peru, we show that lake area in heavily mined watersheds has increased by 670% between 1985 and 2018 and that lakes in this area convert mercury into methylmercury at net rates five to seven times greater than rivers. These results suggest that synergistic increases in lake area and mercury loading associated with ASGM are substantially increasing exposure risk for people and wildlife. Similarly, marked increases in lake area in other ASGM hot spots suggest that "hydroscape" (hydrological landscape) alteration is an important and previously unrecognized component of mercury risk from ASGM.