New research could save seabirds from fishing longlines
The Duke University led researchers have developed a way that locations where boats and birds are most likely to cross over each other can be more precisely identified. Traditional fisheries bycatch models are based almost entirely upon fixed maps of historic bird migration data and past fishery information and there is no consideration of more dynamic factors.
The new models now use biological and physical data, including phytoplankton availability and the temperature of the surface water, which has been remotely sensed. By using this information the scientists can more easily predict how conditions many change to make different areas more suitable for seabird nesting, feeding and other behaviours that are seen at different times within a year. They can then forecast these locations into the future.
Maps of the places where seabirds prefer to live and feed can then be laid over the top of longline fishing activity maps and also maps of bird migration routes. These can ultimately be used by fisheries managers and conservationists to identify places where seabirds may be most at risk of being caught in commercial fishing longlines.
The models were tested in case studies that looked at two pelagic seabird species, the black-footed albatross and the Laysan albatross. These species were chosen because they are known to have migration routes that cross over the Hawaiian swordfish and tuna fisheries. The models highlighted that the Laysan albatross has a suitable habitat in the eastern Pacific along the California Current, even though the historical bird tracking data had not identified this as a location the birds travel to.
The availability of this new information means that conservationists and fishery managers alike can be forewarned about the potential for conflict between seabirds and commercial fishing vessels. Ramunas Zydelis, the lead researcher for the study, says that the case studies confirm that the new models may be especially useful in cases where seabird tracking data does not reflect the full extent of a species current or potential geographic range.
The researchers hope that the new models can be used to reduce the seabird by-catch in fisheries around the world.
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