http://lod.bco-dmo.org/id/dataset/945381
eng; USA
utf8
dataset
Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2024-12-04
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
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)
2025-01-22
publication
2025-01-22
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2025-01-22
publication
https://doi.org/10.26008/1912/bco-dmo.945381.1
Elizabeth North
University of Maryland Center for Environmental Science
principalInvestigator
Archi Howlader
University of Maryland Center for Environmental Science
principalInvestigator
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
publisher
Cite this dataset as: 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 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.945381.1 [access date]
Delaware Bay ACOE Salinity Data Dataset Description: Methods and Sampling: <p>Data collection information from Howlader (2022) “The dataset has continuous near-bottom (1 m off the bottom) measurements of temperature and specific conductivity taken every 30 minutes at the five oyster bed stations from July-December in 2012- 2015 and 2018 using a YSI series 6600EDS V2 data sondes (Bromilow &amp; Wong 2018; Bushek et al. 2014, 2015, 2016). Data sondes were swapped once per month. The depth of water at the monitoring stations were 5-8 meters (Bushek et al. 2014, 2015, 2016).”<br />
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<br />
<br />
&nbsp;</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1756712 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1756712
completed
Elizabeth North
University of Maryland Center for Environmental Science
410-221-8497
5745 Lovers Lane
Cambridge
MD
21613
USA
enorth@umces.edu
pointOfContact
Archi Howlader
University of Maryland Center for Environmental Science
ahowlader@umces.edu
pointOfContact
asNeeded
Dataset Version: 1
Unknown
DATETIME
Salinity
Station
Latitude
Longitude
YSI series 6600EDS V2 data sonde
theme
None, User defined
ISO_DateTime_UTC
salinity
station
latitude
longitude
featureType
BCO-DMO Standard Parameters
YSI Sonde 6-Series
instrument
BCO-DMO Standard Instruments
otherRestrictions
otherRestrictions
Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use.
Collaborative Research: Spatial analysis of genetic differences in salinity tolerance resulting from rapid natural selection in estuarine oysters
https://osprey.bco-dmo.org/project/805117
Collaborative Research: Spatial analysis of genetic differences in salinity tolerance resulting from rapid natural selection in estuarine oysters
<p>NSF abstract:</p>
<p>Many marine animals have a bipartite life cycle consisting of a stationary bottom-dwelling adult stage and a mobile larval stage. The flow of water transports these larval offspring, and their genes, to different habitat patches. It is thought that animals from nearby patches will be more genetically similar than animals in patches that are further in proximity, but these patterns of genetic similarity may not be maintained if the nearby patches have different habitat characteristics. This idea is fundamental to our understanding of adaptation and evolution, but it has not been adequately tested with respect to the effects of rapid selection. This study applies new technologies to test if the genetic signatures of marine animals change even when patches with different environmental characteristics are closer together than the dispersal distance of larvae. This research focuses on eastern oysters (Crassostrea virginica) in Delaware Bay, and their ability to withstand variability in the amount of salt in the water. This study will provide new insights on factors that control oyster survival and growth in estuaries with different salinity profiles. The three investigators are sharing study results with resource managers and stakeholders to improve shellfish restoration and oyster stock management in Delaware Bay, Chesapeake Bay, and New York. A postdoctoral scholar at Cornell and graduate student at the University of Maryland are being trained and mentored during the project. The investigators are also working with teacher training programs in New York and New Jersey to develop and disseminate new curriculum materials on oyster ecology for middle-school students.</p>
<p>The project will investigate whether hyposalinity tolerance of oysters is a function of viability selection during larval dispersal and after settlement. Gene flow across salinity zones within an estuary is expected to be high enough that adaptive differentiation will not result from Darwinian multigenerational processes. Instead, recurrent viability selection in each generation is expected to generate spatial variation in this trait at small spatial scales. This type of recurrent within-generation adaptation has been referred to as phenotype-environment mismatches and has been hypothesized to generate balanced polymorphisms, but it has never been studied beyond single gene cases. The project team is testing for spatially discrete patterns of selection by first collecting oysters from different salinity zones, measuring variation in their tolerance to low salinity and then testing for associations between this trait and genomic variation using whole genome sequencing. Experimental hyposalinity challenges enable within-generation, before/after genomic comparisons to identify DNA variants that change as a result of strong viability selection. Candidate genes and selectively neutral control loci will be assayed in larval, juvenile, and adult samples from the same salinity zones to test for an association between variation at candidate loci and lifetime hyposalinity exposure. Two years of environmental data will be collected and added to an existing long-term data set to map salinity variation. The observed spatial distribution of hyposalinity tolerance and genomic variation associated with it provide a test that could definitively reject the prevalent assumption that all larvae have similar capabilities. If larvae differ by parental source for traits that differentially affect their viability in the plankton, then phenotype-environment mismatches can have profound consequences for population connectivity. This project improves understanding about mechanisms that shape realized larval dispersal and recruitment variation in oyster populations.</p>
<p>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.</p>
SEGO
largerWorkCitation
project
eng; USA
inlandWaters
oceans
-75.5165
-75.248
39.248
39.442
2012-06-05
2018-12-05
Delaware Bay, NJ side of channel: 39.43 N, -75.50 W to 39.14 N, -75.14 W
0
BCO-DMO catalogue of parameters from 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)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
http://lod.bco-dmo.org/id/dataset-parameter/945666.rdf
Name: DATETIME
Units: uniteless
Description: <p>Day and time (UTC) of curated salinity measurement</p>
http://lod.bco-dmo.org/id/dataset-parameter/945667.rdf
Name: Salinity
Units: psu
Description: <p>Curated salinity measuerment (psu) that was shifted by the tidal basis to match the tidal stage at Reedy Point</p>
http://lod.bco-dmo.org/id/dataset-parameter/945668.rdf
Name: Station
Units: unitless
Description: <p>Name of oyster bed station</p>
http://lod.bco-dmo.org/id/dataset-parameter/945669.rdf
Name: Latitude
Units: decimal degrees
Description: <p>Latitude of oyster bed station</p>
http://lod.bco-dmo.org/id/dataset-parameter/945670.rdf
Name: Longitude
Units: decimal degrees
Description: <p>Longitude of oyster bed station</p>
GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
10831841
https://darchive.mblwhoilibrary.org/server/api/core/bitstreams/8ac29a8f-7df6-4cb2-9f07-2e149c418dae/content
download
https://doi.org/10.26008/1912/bco-dmo.945381.1
download
onLine
dataset
<p>Data collection information from Howlader (2022) “The dataset has continuous near-bottom (1 m off the bottom) measurements of temperature and specific conductivity taken every 30 minutes at the five oyster bed stations from July-December in 2012- 2015 and 2018 using a YSI series 6600EDS V2 data sondes (Bromilow &amp; Wong 2018; Bushek et al. 2014, 2015, 2016). Data sondes were swapped once per month. The depth of water at the monitoring stations were 5-8 meters (Bushek et al. 2014, 2015, 2016).”<br />
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<br />
<br />
&nbsp;</p>
Specified by the Principal Investigator(s)
<p>Data curation was conducted on the ACOE datasets to prepare them for analysis (Howlader 2022). All null values were removed and time stamps were converted to the same time zone (UTC/GMT). Comparison datasets used include Station USGS 01482800 Delaware River at Reedy Island Jetty, New Castle County,&nbsp;station USGS 01463500 Delaware River at Trenton, NJ, and&nbsp;Brandywine Shoal Light, NOAA Station ID: 8555889.</p>
<p>Methods description from Howlader (2022):</p>
<p>"Potential instrument malfunctions and fouling problems were investigated in the ACOE dataset. Graphs of daily average salinity at an oyster bed station versus daily average salinity at Reedy were created and visually inspected to identify erroneous measurements caused by sensor malfunction or fouling. Visual inspection revealed that several hundred data points (0.8% of total data set) were substantially lower than most of the data and fell below the 95% prediction interval when a nonlinear model was fit to the data. To determine if these data points were the result of instrument malfunctions or fouling, these data points were plotted against time. Plots (not shown) showed sudden changes in salinity or gradual, linear increases in salinity measurements near the end of a deployment indicative of sensor fouling. To ensure that the anomalous data were due to instrument malfunctions and sensor fouling and not the result of sudden changes in freshwater flow or wind, both freshwater (from station USGS 01463500 Delaware River at Trenton, NJ) and wind (Brandywine Shoal Light, NOAA Station ID: 8555889) data were used. The data were formatted, null values were removed, and data was plotted on the same graph as salinity data to confirm that there were no significant high discharge events coincident with the anomalous salinity observations. Hourly wind data from June-December of 2012 2013, 2014, 2015, and 2018, were likewise plotted with salinity to confirm that there were no strong wind events during the times of the anomalous salinity observations. These analyses demonstrated that the salinity anomalies were most likely a result of sensor fouling and those observations were therefore removed from the dataset."</p>
<p>After removing anomalous data, the data shifted according to the tidal basis using the R package&nbsp;HelpersMG (Girondot, 2015)&nbsp;(from Howlader 2022):&nbsp;</p>
<p>"Each of the ACOE and Haskin time series were shifted by the tidal phase lag and aligned in time to prepare the time series for analysis. Because the Reedy, Hope Creek, Arnolds, Cohansey, Shell Rock, and New Beds stations were located along a transect from upper to lower bay, and the tidal wave progresses from lower to upper bay, the peak in salinity during a tidal period occurred at different times at each station. Shifting the time series by the tidal phase lag corrected this difference. First, the "tide.info" function of the HelpersMG package in R was used to predict the tidal heights (m) at Reedy and the oyster bed stations. The time series of tidal heights were then graphed, and the time difference between peaks (i.e., the tidal phase lag) was calculated. This difference was used to adjust the time series of salinity at the oyster bed stations."</p>
Specified by the Principal Investigator(s)
- imported data from all five location sheets containing corrected data from "Curated ACOE Data.xlsx" into BCO-DMO system
- added station name, lat, and lon for each location referenced
- concatenated all sheets into one dataset
- converted dates to include "Z" - %Y-%m-%dT%H:%MZ
- exported dataset as "945381_v1_acoe_salinity_delaware_bay_2012-2018.csv"
Specified by BCO-DMO Data Managers
asNeeded
7.x-1.1
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
YSI series 6600EDS V2 data sonde
YSI series 6600EDS V2 data sonde
PI Supplied Instrument Name: YSI series 6600EDS V2 data sonde PI Supplied Instrument Description:The dataset has continuous near-bottom (1 m off the bottom) measurements of temperature and specific conductivity taken every 30 minutes at the five oyster bed stations from July-December in 2012- 2015 and 2018 using a YSI series 6600EDS V2 data sondes Instrument Name: YSI Sonde 6-Series Instrument Short Name:YSI Sonde 6-Series Instrument Description: YSI 6-Series water quality sondes and sensors are instruments for environmental monitoring and long-term deployments. YSI datasondes accept multiple water quality sensors (i.e., they are multiparameter sondes). Sondes can measure temperature, conductivity, dissolved oxygen, depth, turbidity, and other water quality parameters. The 6-Series includes several models. More from YSI. Community Standard Description: http://vocab.nerc.ac.uk/collection/L22/current/TOOL0737/