University Events

Description: The School for Marine Science and Technology
Department of Fisheries Oceanography
Seminar Announcement

“Assessing bias in fishing footprints using fine scale data”

Lianne Allen-Jacobson
Department of Fisheries Oceanography

Wednesday, October 12, 2022
2:30 pm to 3:30 pm
SMAST East, Rooms 101/102
And Via Zoom

Abstract:
The U.S. has designated 35,000 square miles of ocean for offshore wind energy development in the northwest Atlantic and this growing industry could impact fisheries in the region. Therefore, we need to measure the spatial distribution of fishing operations to support multiple goals, including marine spatial planning, economic impact, and compensatory mitigation. In the northeast US, NOAA Fisheries previously developed fishing footprints using the spatial buffers around the center point of fishing trips reported in logbooks. We evaluated bias in logbook-footprints by restricting the size of logbook-footprints and by generating active-fishing-footprints from fine-scale global positioning system location data collected by a reference fleet operating in the same region. We focused on the longfin squid (Doryteuthis pealeii) fishery, including 336 trips from 2016 to 2019, and 38 wind farms in southern New England and the Mid-Atlantic Bight. Restricted logbook-footprints detected fewer intersections between wind farms and active-fishing-footprints, compared to non-restricted logbook-footprints. As we restricted logbook-footprints, the analyses predict exposure that approaches predictions using active-fishing-footprints. Finally, logbook-footprints underestimated exposed revenue for high impact wind farms and overestimated exposed revenue for low-impact wind farms, and this bias declines with logbook-footprint restriction. In this case study, we show how restricting logbook-footprints could improve exposure analysis that depends on coarse-scale data when fine-scale data is unavailable. Furthermore, our analysis highlights the limits of coarse-scale data, i.e., logbook-footprints. Therefore, we recommend additional incentives for voluntary participation in programs that collect this fine-scale data. In relation to offshore wind farm construction, informed decisions depend on pre-construction data, so these incentives are time sensitive and should be prioritized.

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Zoom Link
https://umassd.zoom.us/j/93758230260?pwd=OHJ5UDloQkZZaCtXcTlBNlR6Qm0rQT09
Meeting ID: 937 5823 0260
Passcode: 426839

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For additional information, please contact Sue Silva at s1silva@umassd.edu