Geology Reports⌕ Search

USGS · 70025164

Processing watershed-derived nitrogen in a well-flushed New England estuary

Abstract

Isotopically labeled nitrate (15NO3-) was added continuously to the Rowley estuary, Massachusetts, for 22 d to assess the transport, uptake, and cycling of terrestrially derived nitrogen during a period of high river discharge and low phytoplankton activity. Isotopic enrichment of the 3.5-km tidal prism (150,000 m3) was achieved for the 3 weeks and allowed us to construct a nitrogen mass balance model for the upper estuary. Mean ??15NO3- in the estuary ranged from 300??? to 600???, and approximately 75%-80% of the 15N was exported conservatively as 15NO 3- to the coastal ocean. Essentially all of the 20%-25% of the 15N processed in the estuary occurred in the benthos and was evenly split between direct denitrification and autotrophic assimilation. The lack of water-column 15N uptake was attributed to low phytoplankton stocks and short water residence times (1.2-1.4 d). Uptake of water-column NO3- by benthic autotrophs (enriched in excess of 100???) was a function of NO3- concentration and satisfied up to 15% and 25% of the total nitrogen demand for benthic microalgae and macroalgae, respectively. Approximately 10% of tracer assimilated by benthic autotrophs was mineralized and released back to the water column as 15NH4+. By the end of the study, 15N storage in sediments and marsh macrophytes accounted for 50%-70% of the 15N assimilated in the estuary. These compartments may sequester watershed-derived nitrogen in the estuary for time scales of months to years.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

C.R. Tobias, M. Cieri, B. J. Peterson, Linda A. Deegan, J. Vallino, J. Hughes. 2003. Processing watershed-derived nitrogen in a well-flushed New England estuary. https://pubs.usgs.gov/publication/70025164

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Increasing artificial light at night enhances salmonid predator foraging efficiency in an urbanized lake

Artificial light at night (ALAN) poses a threat to ecosystems globally. It includes both direct and indirect light, or skyglow, which occurs when ALAN scatters in the atmosphere, extending beyond its original source. We analyzed ALAN trends in Lake Washington, WA, from 2014 to 2023 using Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light measurements, evaluated the relationship between in situ and satellite measurements, and modeled predator search volumes for a juvenile salmon predator, cutthroat trout ( Oncorhynchus clarki ), as a function of ambient light and turbidity conditions. Open water regions experienced significant increases in ALAN, while nearshore areas primarily showed no or negative trends, revealing the role of skyglow in shaping open water light environments. Using a visual foraging model for cutthroat trout, we found that juvenile salmon at the shallow southern pelagic site experienced light 28 times brighter, resulting in a 168% greater predation vulnerability than those at the northern site. In the Ship Canal, a narrow corridor for outmigrating salmon, predator search volumes were 249% higher than at the southern site. These contrasts in predation vulnerability demonstrate how local conditions influence predator–prey dynamics and provide critical insight for targeting mitigation of both nearshore and distant light sources.

Washington↗

Temperate lake heatwaves accelerate non-linearly as timing synchronizes across a diverse landscape

Temperate lakes are experiencing intensifying heatwaves, or prolonged periods of anomalously warm water, with potentially severe ecological consequences. Previous studies have predominantly used linear trend analyses to understand heatwave dynamics, potentially masking temporal acceleration patterns and shifts in variance. Here, we analyzed long-term, nonlinear trends in heatwave frequency, intensity, and timing across 4391 New York lakes using simulated daily surface water temperatures from an Entity-Aware Long Short-Term Memory deep learning model (validated root mean square error = 1.82°C; 1980–2020). We applied generalized additive mixed models to quantify complex temporal patterns while accounting for lake-specific effects and environmental characteristics (lake surface area, elevation, and latitude). All heatwave metrics demonstrated nonlinear and dynamic temporal trends. Heatwave frequency showed early increases in the number of events (0.05–1.32 events during the 1980s) followed by accelerated growth after 2000; other metrics exhibited more complex decadal patterns. Temporal variance increased significantly for both heatwave frequency ( τ = 0.73, p < 0.001) and intensity ( τ = 0.33, p = 0.003). Lake characteristics drove some heatwave dynamics; smaller lakes experienced higher intensities and complex elevation-latitude interactions varying by heatwave metric. Spatial patterns revealed increasing heterogeneity for heatwave intensity and frequency while heatwave timing homogenized to earlier dates across the landscape. Our findings reveal nonlinear heatwave dynamics with increasing variability, which may reduce predictability and intensify ecological vulnerabilities beyond current projections.

New York↗

Unique thermal mixing patterns in Lake Ontario revealed by novel year-round observations of thermal stratification

Year-round records of thermal stratification in the Great Lakes are rare, and there are few observations of thermal stratification during winter. In this paper, we analyze temperature data from 13 temperature logger chains and from over 130 benthic acoustic receivers that were deployed across Lake Ontario for 2 yr. The timing and duration of the fall overturn correlate with the local average water depth, and shallow sites (< 50 m depth) overturn up to a month before deep sites (> 100 m depths). Likewise, in spring, the shallow sites warm faster. Lake Ontario has partial ice cover, so wind-driven mixing stirs the water column throughout winter, and inverse thermal stratification is largely absent. The depth-averaged winter water temperatures vary between 0°C and 4°C, with the coldest temperatures (near 0.1°C) found in the shallow Kingston basin and warmest temperatures (near 4°C) at sites near the 244 m deep Rochester Basin. Lake Ontario appears to be a warm monomictic lake, rather than having a dimictic mixing pattern as previously described—there is no sustained ice cover or inverse stratification that inhibits vertical mixing in winter. Winter is a poorly understood season for many aquatic processes, including fish bioenergetics, fish distribution, biochemical processes, invertebrate distribution, and production. Moreover, the lack of knowledge of winter has hampered the use of correct initial conditions for running large lake hydrodynamic models.

Lake Ontario↗