Evidence map›Paper›PMID 38432011›Full record

ArticleJournal of environmental management2024

Using monitoring and mechanistic modeling to improve understanding of eutrophication in a shallow New England estuary.

Finnian S Cashel, Christopher D Knightes, Chris Lupo, Traci Iott, Kelly Streich, Corey J Conville, Timothy W Bridges, Ian Dombroski

Abstract read
In one paragraph

Article in Journal of environmental management, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Finnian S CashelOak Ridge Institute for Science and Education Fellow, United States Environmental Protection Agency, Office of Research and Development, Center for Environmental Measurement & Modeling, Atlantic Coastal Environmental Sciences Division, 27 Tarzwell Drive, Narragansett, RI, 02882, USA. Electronic address: Cashel.Finnian@epa.gov.
Christopher D KnightesUnited States Environmental Protection Agency, Office of Research and Development, Center for Environmental Measurement & Modeling, Atlantic Coastal Environmental Sciences Division, 27 Tarzwell Drive, Narragansett, RI, 02882, USA. Electronic address: knightes.chris@epa.gov.
Chris LupoRESPEC, 3825 Jet Dr, Rapid City, SD, 57703, USA. Electronic address: Chris.Lupo@respec.com.
Traci IottConnecticut Department of Energy and Environmental Protection, Bureau of Water Protection and Land Reuse, 79 Elm Street, Hartford, CT, 06106, USA. Electronic address: Traci.Iott@ct.gov.
Kelly StreichConnecticut Department of Energy and Environmental Protection, Bureau of Water Protection and Land Reuse, 79 Elm Street, Hartford, CT, 06106, USA. Electronic address: Kelly.Streich@ct.gov.
Corey J ConvilleUnited States Environmental Protection Agency, Region 1, Laboratory Sciences and Applied Science Divisions, 11 Technology Drive, North Chelmsford, MA, 01863, USA. Electronic address: Conville.Corey@epa.gov.
Timothy W BridgesUnited States Environmental Protection Agency, Region 1, Laboratory Sciences and Applied Science Divisions, 11 Technology Drive, North Chelmsford, MA, 01863, USA. Electronic address: Bridges.Tim@epa.gov.
Ian DombroskiUnited States Environmental Protection Agency, Region 1, Water Division, 5 Post Office Square, Suite 100, Boston, MA, 02109, USA. Electronic address: Dombroski.Ian@epa.gov.

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

Anthropogenic nutrient loading has resulted in eutrophication and habitat degradation within estuaries. Study of eutrophication in estuaries has often focused on larger systems, while there has been increasing interest in understanding the governing processes in smaller systems. In this study, we incorporate both monitoring data and mechanistic modeling to improve our understanding of eutrophication in a small, shallow New England estuary. High-frequency continuous and discrete water quality samples were collected from 2018 to 2020 along a salinity gradient and at varying depth to provide temporal and spatial resolution of the system. Conditions of this estuary were simulated using the Hydrological Simulation Program - FORTRAN (HSPF) and the Water Quality Analysis Simulation Program (WASP) to develop a mechanistic, numerical fate and transport model. Our findings suggest complex hydrodynamics with three distinct salinity gradients and variability in salinity concentration upstream. Simulated and observed nutrient trends demonstrated decreasing total nitrogen concentration moving downstream and low total phosphorus concentration throughout the system. Simulated nutrient depletion and shading via macroalgae suggest their importance in similar modeling initiatives. Dynamic spatiotemporal variability in dissolved oxygen concentrations ([DO]) resulted from hydrodynamic and ecological processes such as large, rapid swings in phytoplankton. Carbonaceous biological oxygen demand was suggested to be the driver of hypoxia in surface waters, while sediment oxygen demand may drive low [DO] in the stratified, benthic waters. These findings suggest that the coordination of monitoring and modeling was important to understanding the governing mechanisms of eutrophication and hypoxia. Insights from this study could be used to support regional management strategies to increase [DO], improve water clarity, and recover indigenous seagrass beds. This work has the potential to inform future study and management of small, complex estuaries.

Indexed as

EstuariesWater QualityEnvironmental MonitoringEutrophicationHumansHypoxiaNew EnglandEutrophicationHypoxiaMacroalgaeNumerical modelingStratification

Identifiers

PMID38432011
PMCPMC11091823

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.