Abstract
Seabirds are facing increasing threats in both marine and terrestrial habitats, and many populations have experienced dramatic declines over past decades. Fisheries bycatch is the most pervasive at-sea threat and is of increasing concern in fisheries management and marine conservation. We predicted spatial and temporal heterogeneities of seabird bycatch probability in the US Atlantic pelagic longline fishery (PLL) through an interactive Barrier model based on observer data from the National Marine Fisheries Service Pelagic Observer Program. The Barrier model prevents bias caused by physical barriers such as coastlines by defining the spatial correlation function as a collection of paths between points and eliminating any paths across physical barriers. The integrated nested Laplace approximations methodology and stochastic partial differential equations approach were applied to fit the model, greatly reducing execution time. Seabird bycatch had a hotspot of high bycatch probability in the mid-Atlantic bight in most years, and the hotspot varied in presence and location yearly. The inter-annual variations in bycatch hotspot are correlated with Gulf Stream meanders. Special area and time fishing restrictions predicted by relationships with Gulf Stream positions might enable the US Atlantic PLL to avoid peak areas and periods of seabird bycatch and thereby support seabird conservation.
Original language | English (US) |
---|---|
Pages (from-to) | 668-679 |
Number of pages | 12 |
Journal | ICES Journal of Marine Science |
Volume | 77 |
Issue number | 2 |
DOIs | |
State | Published - Dec 13 2019 |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledgements: This research was supported by a grant for Modeling Pelagic Longline Seabird Bycatch awarded to YJ by the National Oceanic
and Atmospheric Administration (NOAA), National Marine Fisheries Service Southeast Fisheries Science Center, as part of the
NOAA Fisheries National Seabird Program. The authors acknowledge Advanced Research Computing at Virginia Tech (http://www.arc.vt.edu) for providing computational resources and technical support that have contributed to the results
reported within this article. Attention to the comments of the associate editor and anonymous reviewers led to strengthening of the article