Blue mussel (Mytilus edulis) size frequency data from surveys conducted in coastal eastern Maine from 2014 to 2017 (MuLTI-2 project)

Website: https://www.bco-dmo.org/dataset/720223
Data Type: Other Field Results
Version: 1
Version Date: 2017-12-28

Project
» An integrated theoretical and empirical approach to across-shelf mixing and connectivity of mussel populations (MuLTI-2)
ContributorsAffiliationRole
Yund, Philip O.Downeast Institute for Applied Marine Research and Education (DEI)Principal Investigator, Contact
York, Amber D.Woods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager

Abstract
Blue mussel (Mytilus edulis) size frequency data from surveys conducted in coastal eastern Maine from 2014 to 2017.


Coverage

Spatial Extent: N:44.825311 E:-66.986325 S:44.4644175 W:-68.3045225
Temporal Extent: 2014 - 2017

Dataset Description

Data quantifying temporal patterns in blue mussel (Mytilus edulis) size frequency in large mussel beds in coastal eastern Maine.


Methods & Sampling

Location:  Coastal waters of eastern Maine, from Frenchman Bay to the Canadian border. Locations and descriptions for station codes used in this dataset can be found in the dataset: MuLTI-2 Mussel Station List

Sampling and Analytical Methodology: 

Size frequencies of blue mussels (Mytilus edulis) were measured at three random sample locations at each of the major mussel beds (stations) along the eastern Maine coast from Frenchman Bay to the Canadian border. At each sample location, a 30 cm x 30 cm quadrat was laid down haphazardly in a relatively dense patch of mussels, and the entirety of the quadrat contents harvested (byssal thread matrix and soft-sediment included). If <30 individual mussels were in the quadrat, further samples were taken immediately adjacent to the original quadrat until 30+ mussels had been harvested. The contents of each sample was returned to the lab for careful sorting into 5 mm size class bins. The number of mussels within each size class bin were enumerated and the frequency of each size class in each sample was calculated yielding three frequencies per size class per year per mussel population.

Size Class Frequency was calculated as the Count of Individual Mussels within a particular size class divided by the Total Individual Mussels Sampled within a plot.


Data Processing Description

BCO-DMO Data Manager Processing Notes:
* added a conventional header with dataset name, PI name, version date
* modified parameter names to conform with BCO-DMO naming conventions
* Problem in 2017 data where some size classes were formatted as dates (e.g. 10-May -> 5 - 10). Communicated with data contributor and corrected.


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Data Files

File
SizeFreq.csv
(Comma Separated Values (.csv), 199.32 KB)
MD5:a057fd2e2b3b433cbfa0199904697070
Primary data file for dataset ID 720223

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Parameters

ParameterDescriptionUnits
Sampling_Event

Identifier of sampling event

unitless
Station_Code

Identifier of sampling station

unitless
Sample_Year

Year of sampling event

unitless
Replicate_Plot

Replicate plot number

unitless
Size_Class

Blue mussel (Mytilus edulis) size class. Size class is described as a mm size range (e.g. "10 - 15"). Mussels were counted if the length was >= the minimum bounding size and < the maximum bounding size

millimeters (mm)
Mussel_Count

Number of Blue mussels (Mytilus edulis) in size class within plot

per individual
Mussels_Sampled

Total mussels sampled within a plot

per individual
Size_Class_Freq

Size class frequency. The count of individual mussels within a particular size class divided by the total individual mussels sampled within a plot (Mussel_Count/Mussels_Sampled)

dimensionless

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Deployments

MuLTI-2_Mussel_Sampling

Website
Platform
Maine_Coast
Start Date
2014-04-24
Description
These locations were sampled using The Uglement, an automobile.  Mussel Gonad Index (GI), size frequency, settlement, and density were surveyed.


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Project Information

An integrated theoretical and empirical approach to across-shelf mixing and connectivity of mussel populations (MuLTI-2)

Coverage: Gulf of Maine: Frenchmen Bay (44 28.239 N -68 15.927 W) to Machais Bay (44 39.350 N -67 21.320 W)


Acronym "MuLTI-2" (Mussel Larval Transport Initiative-2)

Extracted from the NSF award abstract:

Existing larval transport models focus mainly on along-shelf transport and have done little to explicitly incorporate the effects of cross-shelf mixing and transport processes. Yet cross-shelf transits (both outgoing and incoming legs) are critical components of the dispersal paths of coastal invertebrates. This project will explore the role of cross-shelf mixing in the connectivity of blue mussel populations in eastern Maine. Previous work has shown that the Eastern Maine Coastal Current (EMCC) begins to diverge from shore southwest of the Grand Manan Channel and creates a gradient in cross-shelf mixing and larval transport, with cross-shelf mixing being more common on the northeastern end, episodic in the transitional middle area, and then becoming rare in the southwestern half of the region of the Gulf of Maine. As a result, the investigators predict that northeastern populations of mussels are seeded mostly from up-stream sources, while a significant component of self-seeding (local retention) exists in southwestern populations. Larvae settling in the intervening bays are expected to be derived from a mixture of local and up-stream sources. Using a combined empirical and theoretical approach hydrographic, current profile, and larval vertical migration data will be collected and used to develop and validate a high-resolution coastal circulation model coupled to a model of larval behavior. The investigators will model simulations in different years using the empirical data from mussel reproductive output and spawning times. Connectivity predicted from this model will be then tested against independent empirical estimates of connectivity based on trace element fingerprinting for larvae which can be connected to specific natal habitats. Regions of agreement and discrepancy in the model will be identified to guide additional data collection and model refinement. This iterative process will ensure an understanding of both larval transport patterns and processes, and provide estimates of inter-annual variability in connectivity for blue mussel populations in the Gulf of Maine.



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Funding

Funding SourceAward
NSF Division of Ocean Sciences (NSF OCE)

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