Scup and windowpane flounder expanded length frequency for study of scup and windowpane flounder catch using scup gear and a Large Mesh Belly Panel (LMBP), October 2015 (Windowpane Bycatch project)

Website: https://www.bco-dmo.org/dataset/686700
Data Type: Cruise Results
Version: 1
Version Date: 2017-03-16

Project
» Small Mesh Fishery Bycatch Reduction in the Southern New England/Mid-Atlantic Windowpane Flounder Stock Area (Windowpane Bycatch)

Program
» NorthEast Consortium (NEC)
ContributorsAffiliationRole
Hasbrouck, Emerson CCornell University (Cornell)Principal Investigator
Gerbino, KristinCornell University (Cornell)Contact
Copley, NancyWoods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager

Abstract
This dataset reports the length frequency count of scup and windowpane flounder caught in each haul. Data was collected from paired tows to determine if a large mesh belly panel effectively reduces the catch of windowpane flounder in the small mesh scup fishery with existing gear and fishing practices. The data was analyzed to determine the statistical level of difference between the control and experimental nets for the targeted scup catch and for the windowpane flounder catch, should a difference exist.


Coverage

Spatial Extent: N:41.3333 E:-70.6667 S:40.8333 W:-71.5
Temporal Extent: 2015-10-07 - 2015-10-21

Methods & Sampling

Hauls were made in southern New England marine waters encompassing approximately 2000 square miles extending from Point Judith, RI in the west to Martha’s Vineyard, MA in the east and extending south to include Rhode Island Sound and portions of the Atlantic Ocean.

Subsamples of the catch were taken during each tow for length frequency distribution analysis. For each tow, 100 individual length measurements were taken for scup and windowpane flounder. All fish were measured if there were less than 100 per tow. The subsample length frequencies were expanded to the entire catch to determine the length frequency distribution for the catch. For each tow, the total catch numbers at length were calculated as the subsample numbers at length multiplied by the species-specific ratio of catch weight to subsample weight. Catch numbers were calculated for each net as the sum of the expanded numbers at length per tow.

The methodology is available in the final report (pdf). See Supplemental Files section.


Data Processing Description

BCO-DMO Processing Notes:
- added conventional header with dataset name, PI name, version date
- modified parameter names to conform with BCO-DMO naming conventions
- reduced number of significant digits of ratio (wgt_total_to_wgt_subsample) due to math precision rules


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Data Files

File
expanded_lens.csv
(Comma Separated Values (.csv), 21.08 KB)
MD5:7902c4588768ca2a26f2e19e2f47045a
Primary data file for dataset ID 686700

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Supplemental Files

File
Small Mesh Fishery Bycatch Reduction in the Southern New England/Midatlantic Windowpane Stock Area
filename: CCE_Windowpane_Scup_Final_Report_111516.pdf
(Portable Document Format (.pdf), 4.83 MB)
MD5:ca92acdd509050168719dff5050eee77
A Final Report to The Northeast Consortium and The New England Fishery Management Council Groundfish Research Program Agreement No. 15-033 Period of Performance: 3/1/15 – 8/31/16

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Related Datasets

IsRelatedTo
Hasbrouck, E. C. (2021) Scup and windowpane flounder length frequency count for study of windowpane flounder catch using scup gear and a Large Mesh Belly Panel (LMBP), October 2015 (Windowpane Bycatch project). Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2017-03-16 doi:10.26008/1912/bco-dmo.686539.1 [view at BCO-DMO]
Hasbrouck, E. C. (2021) Scup and windowpane flounder length frequency for study of windowpane flounder catch using scup gear and a Large Mesh Belly Panel (LMBP), October 2015 (Windowpane Bycatch project). Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2017-03-16 doi:10.26008/1912/bco-dmo.685559.1 [view at BCO-DMO]
Hasbrouck, E. C. (2021) Tow log and catch for study of windowpane flounder catch using scup gear and a Large Mesh Belly Panel (LMBP), October 2015 (Windowpane Bycatch project). Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2017-03-16 doi:10.26008/1912/bco-dmo.685079.1 [view at BCO-DMO]

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Parameters

ParameterDescriptionUnits
trip

trip number

unitless
tow

tow number

unitless
treatment

Control net or net with large mesh belly panel

unitless
species

fish species: scup or windowpane flounder

unitless
count

Number of fish measured in subsample

fish
wgt_fish_avg

average weight of individual scup or windowpane flounder calculated by dividing 'Count' by 'Total Pounds'

pounds
sp_catch_lb

species specific total catch weight

pounds
wgt_subsample

weight of species-specific subsample

pounds
wgt_total_to_wgt_subsample

ratio of the species-specific total catch weight to the subsample weight

pounds
len_4cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_5cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_6cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_7cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_8cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_9cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_10cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_11cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_12cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_13cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_14cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_15cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_16cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_17cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_18cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_19cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_20cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_21cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_22cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_23cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_24cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_25cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_26cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_27cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_28cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_29cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_30cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_31cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_32cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_33cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_34cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_35cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_36cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_37cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_38cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish
len_39cm

weight of fish in this length bin for entire catch; calculated by multiplying fish in length bin from the length frequency dataset by the species specific catch (wgt_total_to_wgt_subsample)

fish


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Instruments

Dataset-specific Instrument Name
Generic Instrument Name
Trawl_custom
Dataset-specific Description
Experimental net with the large mesh belly panel and small mesh typical of that used in scup fishery along the East Coast of the US. The nets used for this project were 286 x 16cm, 4-seam, 3-bridle standard otter trawls. The 286 x 16cm refers to the circumference of the fishing circle (286 meshes around of 16 cm mesh to form the circle) and nets of this size are appropriate for vessels with horsepower in the range of 400hp to 550hp. The net was constructed with 16cm (full mesh) webbing in the wings and jibs. The bunt and the 1st bottom belly were constructed from 12 cm mesh. The top square, top bellies, and the side panels were constructed from 8cm Dyneema webbing. The last belly section, top, and bottom were 6cm PE webbing. The codend was constructed of 5" regulation mesh used in the scup fishery. Flotation for this trawl was provided by 48 -8" floats mounted on the headrope. The sweep of the trawl was constructed of 2-3/8" and 3" rubber discs on wire rope. The sweep was comprised of three pieces totaling 2400cm or 78.72 feet in length. The headrope height was approximately 16 feet high. This net was then modified by Jon Knight of Superior Trawl to include the LMBP. The large mesh panel for this project was made from 5mm poly webbing and the mesh size was 80cm or approximately 32 inches knot-center to knot-center diamond mesh. The actual panel was 2 meshes deep and was sewn into the standard 12cm (5”) mesh of the 1st bottom belly using a "saw-toothing" technique. Similar to the SNECRI project, this results in an effective area for fish escapement of 3 full 32 inch meshes, or an opening in the belly of the net that is approximately 8 feet deep from front to back. The LMBP attached approximately 1 foot (2.5 meshes/12cm) behind the footrope and extended widthwise across the entire belly of the net (from gore to gore) for 30 meshes of 32 inch diamond mesh.
Generic Instrument Description
A net towed through the water column designed to sample free-swimming nekton or fish, varies in design depending on the research project.


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Deployments

Sea_Breeze_Too-trip1

Website
Platform
F/V Sea Breeze Too
Start Date
2015-10-07
End Date
2015-10-09
Description
fishing gear studies

Methods & Sampling
This dataset combines trip 1 from Katherine & Elizabeth and Sea Breeze Too.

Sea_Breeze_Too-trip2

Website
Platform
F/V Sea Breeze Too
Start Date
2015-10-15
End Date
2015-10-15
Description
fishing gear studies

Methods & Sampling
This dataset combines trip 2 from Katherine & Elizabeth and Sea Breeze Too.

Sea_Breeze_Too-trip3

Website
Platform
F/V Sea Breeze Too
Start Date
2015-10-18
End Date
2015-10-19
Description
fishing gear studies

Methods & Sampling
This dataset combines trip 3 from Katherine & Elizabeth and Sea Breeze Too.

Sea_Breeze_Too-trip4

Website
Platform
F/V Sea Breeze Too
Start Date
2015-10-21
End Date
2015-10-21
Description
fishing gear studies

Methods & Sampling
This dataset combines trip 4 from Katherine & Elizabeth and Sea Breeze Too.

Elizabeth_and_Katherine-trip1

Website
Platform
F/V Elizabeth & Katherine
Start Date
2015-10-07
End Date
2015-10-09
Description
fishing gear studies

Methods & Sampling
This dataset combines trip 1 from Katherine & Elizabeth and Sea Breeze Too.

Elizabeth_and_Katherine-trip2

Website
Platform
F/V Elizabeth & Katherine
Start Date
2015-10-15
End Date
2015-10-15
Description
fishing gear studies

Methods & Sampling
This dataset combines trip 2 from Katherine & Elizabeth and Sea Breeze Too.

Elizabeth_and_Katherine-trip3

Website
Platform
F/V Elizabeth & Katherine
Start Date
2015-10-18
End Date
2015-10-19
Description
fishing gear studies

Methods & Sampling
This dataset combines trip 3 from Katherine & Elizabeth and Sea Breeze Too.

Elizabeth_and_Katherine-trip4

Website
Platform
F/V Elizabeth & Katherine
Start Date
2015-10-21
End Date
2015-10-21
Description
fishing gear studies

Methods & Sampling
This dataset combines trip 4 from Katherine & Elizabeth and Sea Breeze Too.


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Project Information

Small Mesh Fishery Bycatch Reduction in the Southern New England/Mid-Atlantic Windowpane Flounder Stock Area (Windowpane Bycatch)


Coverage: Southern New England


Extracted from the NSF award abstract:

Currently, bycatch of windowpane flounder in the northwestern Atlantic is a concern of fishery management. Exceeding the Annual Catch Limit (ACL) for windowpane has the potential to trigger Accountability Measures that restrict fishing activities. This project sought to enhance the opportunity for fishermen to fully access ACLs by validating the effectiveness of an innovative gear modification. CCE tested and evaluated a large mesh belly panel for use as an avoidance gear to reduce windowpane flounder bycatch in small mesh trawl fisheries in Southern New England. Statistical analysis of the data indicated that there was a significant reduction in catch of windowpane flounder in the control net compared to the experimental net with the large mesh belly panel when analyzed in terms of both catch weights and in number of individual fish.

A Final Report to The Northeast Consortium and The New England Fishery Management Council Groundfish Research Program (PDF)



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Program Information

NorthEast Consortium (NEC)


Coverage: Georges Bank, Gulf of Maine


The Northeast Consortium encourages and funds
cooperative research and monitoring projects in the Gulf of Maine and Georges Bank that have effective,
equal partnerships among fishermen, scientists, educators, and marine resource managers.

At the 2008 Maine Fisheremen's Forum, the Northeast Consortium organized a session on data collection and availability. Participants included several key organizations in the Gulf of Maine area, sharing what data are out there and how you can find them. 

The Northeast Consortium has joined the Gulf of Maine Ocean Data Partnership. The purpose of the GoMODP is to promote and coordinate the sharing, linking, electronic dissemination, and use of data on the Gulf of Maine region.

The Northeast Consortium was created in 1999 to encourage and fund effective, equal partnerships among commercial fishermen, scientists, and other stakeholders to engage in cooperative research and monitoring projects in the Gulf of Maine and Georges Bank. The Northeast Consortium consists of four research institutions (University of New Hampshire, University of Maine, Massachusetts Institute of Technology, and Woods Hole Oceanographic Institution), which are working together to foster this initiative.

The Northeast Consortium administers nearly $5M annually from the National Oceanic and Atmospheric Administration for cooperative research on a broad range of topics including gear selectivity, fish habitat, stock assessments, and socioeconomics. The funding is appropriated to the National Marine Fisheries Service and administered by the University of New Hampshire on behalf of the Northeast Consortium. Funds are distributed through an annual open competition, which is announced via a Request for Proposals (RFP). All projects must involve partnership between commercial fishermen and scientists.

The Northeast Consortium seeks to fund projects that will be conducted in a responsible manner. Cooperative research projects should be designed to minimize any negative impacts to ecosystems or marine organisms, and be consistent with accepted ethical research practices, including the use of animals and human subjects in research, scrutiny of research protocols by an institutional board of review, etc.



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Funding

Funding SourceAward
NorthEast Consortium (NEC)

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