Discards from commercial fisheries have been linked to detrimental effects on ecosystems and stocks of living marine resources. Understanding spatial and temporal patterns of discards may assist in devising regulatory practices and mitigation strategies and promote sustainable management policies. This study investigates data from bycatch monitoring programs using a machine learning approach. We used a gradient boosting classifier for describing catch and bycatch patterns in the U.S. Mid-Atlantic Black Seabass (Centropristis striata), Summer Flounder (Paralichthys dentatus), Scup (Stenotomus chrysops), and Longfin Squid (Doryteuthis pealeii) fisheries. We used oceanographic, biological, spatial, and fisheries data as explanatory model features. We found positive associations between target species volume and bycatch. Although we found that sea surface temperature and year were important model features, the direction of impact of those predictors was variable. From our findings, we conclude that machine learning approaches are promising in supplementing traditional methodologies, especially with the increase in data availability trends.
- Home
- Search Results
- Page 1 of 1
Search for: All records
-
Total Resources4
- Resource Type
-
00040
- Availability
-
31
- Author / Contributor
- Filter by Author / Creator
-
-
Riedel, Ralf (4)
-
Ionescu, Emanuel (3)
-
Kroll, Peter (2)
-
Aguirre, Trevor G. (1)
-
Bernard, Samuel (1)
-
Bhat, Shrikant (1)
-
Colombo, Paolo (1)
-
Cramer, Corson L. (1)
-
Farla, Robert (1)
-
Glazyrin, Konstantin (1)
-
Gollé‐Leidreiter, Philipp (1)
-
Graczyk-Zajac, Magdalena (1)
-
Haseen, Shariq (1)
-
Haslam, Jeffery J. (1)
-
Katoh, Yutai (1)
-
Katsura, Tomoo (1)
-
Kolb, Ute (1)
-
LeBlanc, Saniya (1)
-
Lucas, Romain (1)
-
Masoudi, Mansour (1)
-
- Filter by Editor
-
-
& Spizer, S. M. (0)
-
& . Spizer, S. (0)
-
& Ahn, J. (0)
-
& Bateiha, S. (0)
-
& Bosch, N. (0)
-
& Brennan K. (0)
-
& Brennan, K. (0)
-
& Chen, B. (0)
-
& Chen, Bodong (0)
-
& Drown, S. (0)
-
& Ferretti, F. (0)
-
& Higgins, A. (0)
-
& J. Peters (0)
-
& Kali, Y. (0)
-
& Ruiz-Arias, P.M. (0)
-
& S. Spitzer (0)
-
& Spitzer, S. (0)
-
& Spitzer, S.M. (0)
-
(submitted - in Review for IEEE ICASSP-2024) (0)
-
- (0)
-
-
Have feedback or suggestions for a way to improve these results?
!
Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher.
Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?
Some links on this page may take you to non-federal websites. Their policies may differ from this site.
-
Free, publicly-accessible full text available December 18, 2024
-
Cramer, Corson L. ; Ionescu, Emanuel ; Graczyk-Zajac, Magdalena ; Nelson, Andrew T. ; Katoh, Yutai ; Haslam, Jeffery J. ; Wondraczek, Lothar ; Aguirre, Trevor G. ; LeBlanc, Saniya ; Wang, Hsin ; et al ( , Journal of the European Ceramic Society)
-
Ionescu, Emanuel ; Bernard, Samuel ; Lucas, Romain ; Kroll, Peter ; Ushakov, Sergey ; Navrotsky, Alexandra ; Riedel, Ralf ( , Advanced Engineering Materials)
-
Bhat, Shrikant ; Wiehl, Leonore ; Haseen, Shariq ; Kroll, Peter ; Glazyrin, Konstantin ; Gollé‐Leidreiter, Philipp ; Kolb, Ute ; Farla, Robert ; Tseng, Jo‐Chi ; Ionescu, Emanuel ; et al ( , Chemistry – A European Journal)