Examining the frontier of autonomous underwater vehicle image analysis for sea scallop incidental mortality

dc.contributor.authorTipton, Hunter
dc.date.accessioned2022-02-21T12:58:57Z
dc.date.available2022-02-21T12:58:57Z
dc.date.issued2021
dc.date.updated2021-09-30T19:14:32Z
dc.description.abstractHistorically, the Atlantic sea scallop (Placopecten magellanicus) fishery in the United States has undergone vast changes in management to combat stock volatility and fishing pressure. Today the American sea scallop stock has stabilized and is successfully managed via fishery independent surveys and stock assessment models. One of the factors affecting the stock assessment model for this fishery is incidental fishing mortality, or those individual scallops that experience mortality because of fishing effort but are not retained for use by the fishery. Recent studies sought to enumerate sea scallop incidental mortality on various seabed types. However, most of the scallops examined in these studies were inhabiting sandy bottoms more generally known as soft substrate. This study utilized 38,813 underwater images collected via Autonomous Underwater Vehicle (AUV) and a modified Multiple Before After Control Impact (MBACI) experimental design to examine incidental mortality on gravel and rock, or hard substrates within Closed Area I just north of the great south channel. Of the 31,972 scallops measured from these images 73% were annotated as lying on hard substrate and the highest measured value of incidental mortality was 6.70%. This result suggests that stock assessment values for incidental mortality remain conservative for hard substrate management areas. The results of this study also suggest that both sediment and sea scallop distributions may be more variable than previously understood within the spatial domain of a study site.en_US
dc.description.advisorTrembanis, Arthur C.
dc.description.degreeM.S.
dc.description.departmentUniversity of Delaware, School of Marine Science and Policy
dc.identifier.doihttps://doi.org/10.58088/3krc-8q35
dc.identifier.unique1298584542
dc.identifier.urihttps://udspace.udel.edu/handle/19716/30447
dc.language.rfc3066en
dc.publisherUniversity of Delawareen_US
dc.relation.urihttps://login.udel.idm.oclc.org/login?url=https://www.proquest.com/dissertations-theses/examining-frontier-autonomous-underwater-vehicle/docview/2591387741/se-2?accountid=10457
dc.subjectAtlantic sea scallop
dc.subjectAutonomous underwater vehicle
dc.subjectDeep learning
dc.subjectImage analysis
dc.subjectMultiple bore after control impact
dc.titleExamining the frontier of autonomous underwater vehicle image analysis for sea scallop incidental mortalityen_US
dc.typeThesisen_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Tipton_udel_0060M_14741.pdf
Size:
2.28 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
2.22 KB
Format:
Item-specific license agreed upon to submission
Description: