Department of Fisheries Oceanography-PhD Dissertation Defense by Brooke Lowman
When: Thursday,
August 26, 2021
9:00 AM
-
10:00 AM
Where: > See description for location
Description: The School for Marine Science and Technology
Department of Fisheries Oceanography
PhD Dissertation Defense Announcement
"Analysis of Fishery Dependent Data to Support Fishery Management"
A Dissertation in Marine Science and Technology-Living Marine Resources Science and Management
by
Brooke A. Lowman
Advisor:
Steven Cadrin, Department of Fisheries Oceanography, SMAST at University of Massachusetts Dartmouth
Committee:
Gavin Fay, Department of Fisheries Oceanography, SMAST at University of Massachusetts Dartmouth
Avijit Gangopadhyay, Department of Estuarine and Ocean Sciences, SMAST at University of Massachusetts Dartmouth
Cate O'Keefe, Fishery Applications Consulting Team
N. David Bethoney, Commercial Fisheries Research Foundation
Thursday, August 26, 2021
9:00 am to 10:00 am
SMAST East, Rooms 101, 102, 103
Also via Zoom
Abstract - Fishery dependent data is a critical component of understanding population and fishery dynamics. Beyond catch monitoring and stock assessments, there are opportunities to use fishery dependent data in developing fishery management options, supporting decisions, and achieving management objectives. Three case studies in the Northeast U.S. are presented to illustrate novel uses of fishery dependent data. In the first case study, fishermen’s insights informed factors to consider for developing a generalized linear model of landings per unit effort (LPUE) in the U.S. Atlantic sea scallop (Placopecten magellanicus) fishery. The model is presented in the context of predicting the LPUE for use in annual days-at-sea allocations for the fishery. With expert judgment to make more informed assumptions, this tool could be used to provide an alternate approach for projecting LPUE. The second case study is an evaluation of a bycatch avoidance program in the U.S. Atlantic sea scallop fishery. Data from the avoidance program and at-sea observers were analyzed using loglinear models to identify patterns of fishing behavior by program participants and non-participants through time. Results demonstrated differences in the fishing behavior of fishing captains who participated in the bycatch avoidance program when yellowtail flounder bycatch was perceived to threaten economic yield due to fishery closures. Finally, the impact of the U.S. Mid-Atlantic northern shortfin squid (Illex illecebrosus) fishery on the stock is approximated based on the overlap of occupied area (as estimated by a species distribution model) and fishery footprint. The findings suggest a limited degree of overlap between the US fishery and the modeled area occupied by the squid on the US continental shelf. In conclusion, the dissertation demonstrates a variety of nonconventional applications of fishery monitoring data to support fishery management and decisions for sustainable fishing.
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Meeting ID: 973 5985 7355
Passcode: 834928
****************************************************************************
For additional information, please contact Sue Silva at s1silva@umassd.edu.
Department of Fisheries Oceanography
PhD Dissertation Defense Announcement
"Analysis of Fishery Dependent Data to Support Fishery Management"
A Dissertation in Marine Science and Technology-Living Marine Resources Science and Management
by
Brooke A. Lowman
Advisor:
Steven Cadrin, Department of Fisheries Oceanography, SMAST at University of Massachusetts Dartmouth
Committee:
Gavin Fay, Department of Fisheries Oceanography, SMAST at University of Massachusetts Dartmouth
Avijit Gangopadhyay, Department of Estuarine and Ocean Sciences, SMAST at University of Massachusetts Dartmouth
Cate O'Keefe, Fishery Applications Consulting Team
N. David Bethoney, Commercial Fisheries Research Foundation
Thursday, August 26, 2021
9:00 am to 10:00 am
SMAST East, Rooms 101, 102, 103
Also via Zoom
Abstract - Fishery dependent data is a critical component of understanding population and fishery dynamics. Beyond catch monitoring and stock assessments, there are opportunities to use fishery dependent data in developing fishery management options, supporting decisions, and achieving management objectives. Three case studies in the Northeast U.S. are presented to illustrate novel uses of fishery dependent data. In the first case study, fishermen’s insights informed factors to consider for developing a generalized linear model of landings per unit effort (LPUE) in the U.S. Atlantic sea scallop (Placopecten magellanicus) fishery. The model is presented in the context of predicting the LPUE for use in annual days-at-sea allocations for the fishery. With expert judgment to make more informed assumptions, this tool could be used to provide an alternate approach for projecting LPUE. The second case study is an evaluation of a bycatch avoidance program in the U.S. Atlantic sea scallop fishery. Data from the avoidance program and at-sea observers were analyzed using loglinear models to identify patterns of fishing behavior by program participants and non-participants through time. Results demonstrated differences in the fishing behavior of fishing captains who participated in the bycatch avoidance program when yellowtail flounder bycatch was perceived to threaten economic yield due to fishery closures. Finally, the impact of the U.S. Mid-Atlantic northern shortfin squid (Illex illecebrosus) fishery on the stock is approximated based on the overlap of occupied area (as estimated by a species distribution model) and fishery footprint. The findings suggest a limited degree of overlap between the US fishery and the modeled area occupied by the squid on the US continental shelf. In conclusion, the dissertation demonstrates a variety of nonconventional applications of fishery monitoring data to support fishery management and decisions for sustainable fishing.
****************************************************************************
Join Zoom Meeting
https://umassd.zoom.us/j/97359857355?pwd=ZGdUVS9aUTF1dDBRUkYwTkpLcWR5QT09
Meeting ID: 973 5985 7355
Passcode: 834928
One tap mobile
+13017158592,,97359857355#,,,,*834928# US (Washington DC)
+13126266799,,97359857355#,,,,*834928# US (Chicago)
Dial by your location
+1 301 715 8592 US (Washington DC)
+1 312 626 6799 US (Chicago)
+1 646 876 9923 US (New York)
+1 253 215 8782 US (Tacoma)
+1 346 248 7799 US (Houston)
+1 669 900 6833 US (San Jose)
Meeting ID: 973 5985 7355
Passcode: 834928
Find your local number: https://umassd.zoom.us/u/av882Odst
Join by SIP
97359857355@zoomcrc.com
Join by H.323
162.255.37.11 (US West)
162.255.36.11 (US East)
115.114.131.7 (India Mumbai)
115.114.115.7 (India Hyderabad)
213.19.144.110 (Amsterdam Netherlands)
213.244.140.110 (Germany)
103.122.166.55 (Australia Sydney)
103.122.167.55 (Australia Melbourne)
149.137.40.110 (Singapore)
64.211.144.160 (Brazil)
149.137.68.253 (Mexico)
69.174.57.160 (Canada Toronto)
65.39.152.160 (Canada Vancouver)
207.226.132.110 (Japan Tokyo)
149.137.24.110 (Japan Osaka)
Meeting ID: 973 5985 7355
Passcode: 834928
****************************************************************************
For additional information, please contact Sue Silva at s1silva@umassd.edu.
Contact: > See Description for contact information
Topical Areas: School for Marine Sciences and Technology, SMAST Seminar Series