Dataset: Salinity data collected from near-bottom HOBO logger placed in oyster beds in the Delaware Bay Apr 2021 to Nov 2021 (SEGO project)

ValidatedFinal no updates expectedDOI: 10.26008/1912/bco-dmo.945362.1Version 1 (2024-12-10)Dataset Type:Cruise ResultsDataset Type:Other Field Results

Principal Investigator: Elizabeth North (University of Maryland Center for Environmental Science)

Scientist: Archi Howlader (University of Maryland Center for Environmental Science)

BCO-DMO Data Manager: Audrey Mickle (Woods Hole Oceanographic Institution)


Project: Collaborative Research: Spatial analysis of genetic differences in salinity tolerance resulting from rapid natural selection in estuarine oysters (SEGO)


Abstract

Salinity data was collected at three stations (Hope Creek, Cohansey, and New Beds) in the Delaware River from May to November, 2021 as part of the Selection along Estuarine Gradients in Oysters (SEGO) project. Data loggers were suspended near-bottom and swapped out monthly to provide a timeseries of near-bottom salinity at the three stations. Dr. Daphne Munroe led the collection of this data on the research cruise conducted by Rutgers University on the R/V Bivalve. This dataset was curated by gr...

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Field measurements of salinity were collected as part of the Selection along Estuarine Gradients in Oysters (SEGO) project. HOBO Saltwater Conductivity Data Loggers (HOBO U24-002-C) were fixed to a frame and suspended in the water about 5-10 cm off the bottom from May to November 2021 at the Hope Creek, Cohansey, and New Beds stations (Manuel 2022). These data loggers stored measurements of conductivity and temperature every 15 minutes. Sensors were swapped out on a monthly basis during summer and a calibrated YSI sensor was used to take measurements near the sensor in situ to check sensor accuracy upon deployment and retrieval. Data loggers at the Cohansey station were lost halfway through the deployment period. Data were formatted for analysis and screened for instrument malfunctions and fouling problems. This field data was important for model validation because it was collected after the dredging was complete in the Delaware River navigational channel (conducted from 2012 and 2018) that could have affected the salinity regime. Daphne Munroe and Jenn Gius at Rutgers University conducted the field sampling. 

In the SEGO dataset, biofouling and sediment deposition on HOBO sensors influenced the accuracy of the salinity measurements, likely because sensors were deployed only 5-10 cm above the oyster beds. Inspection of time series plots, comparison of data with YSI sensors, and comparison of data with freshwater discharge records were conducted, similar to the quality assurance methods for the ACOE dataset. Sensor fouling was a more significant problem than in the ACOE dataset (see related datasets), with 35%, 8%, and 57% of data being discarded at Hope Creek, Cohansey, and New Beds stations, respectively. Archi Howlader at University of Maryland Center for Environmental Science conducted the data curation (Howlader 2022).


Related Datasets

IsRelatedTo

Dataset: Delaware Bay ACOE Salinity Data
Howlader, A., North, E. (2025) Salinity data collected by the Army Corps of Engineers (ACOE) from near-bottom sondes placed in oyster beds in the Delaware Bay from 2012 to 2018 (SEGO project). Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2025-01-22 doi:10.26008/1912/bco-dmo.945381.1

Related Publications

Results

Howlader, A., North, E. W., Munroe, D., & Hare, M. P. (2024). Hindcasting Estuarine Bottom Salinity Using Observing Systems Data and Nonlinear Regression, as Applied to Oysters in Delaware Bay. Estuaries and Coasts, 47(8), 2341–2359. https://doi.org/10.1007/s12237-024-01396-x
Results

Howlader, Archi (2022). Predicting the Salinity History of Oysters in Delaware Bay Using Observing Systems Data and Nonlinear Regression. <i>Digital Repository at the University of Maryland</i>. https://doi.org/10.13016/CRJQ-2VKB
Methods

Hill, K., Dauphinee, T., & Woods, D. (1986). The extension of the Practical Salinity Scale 1978 to low salinities. IEEE Journal of Oceanic Engineering, 11(1), 109–112. https://doi.org/10.1109/joe.1986.1145154
Methods

Manuel, E. C., Hare, M. P., & Munroe, D. (2023). Consequences of Salinity Change, Salinity History, and Shell Morphology on Early Growth of Juvenile Oysters. Journal of Shellfish Research, 42(1). https://doi.org/10.2983/035.042.0103
Software

Jassby, A. (2017). wql: Exploring Water Quality Monitoring Data [dataset]. In CRAN: Contributed Packages. The R Foundation. https://doi.org/10.32614/cran.package.wql