Abstract Title

Session S-10E: Evaluation, Conservation and Restoration of Species Associated with High-Relief, Rocky Habitat in the Salish Sea

Proposed Abstract Title

Derelict Gillnets in the Salish Sea: Causes of Gillnet Loss, Extent of Accumulation and Development of a Predictive Transboundary Model

Keywords

Species and Food Webs

Location

Room 613-614

Start Date

2-5-2014 1:30 PM

End Date

2-5-2014 3:00 PM

Description

From 2002 through the end of 2012, a total of 4,358 derelict nets were removed from the Washington waters of the Salish Sea (WASS), 95% of which were gillnets. Forty-five percent of these gillnets were removed from low to high relief rocky substrate. I investigated the causes and rates of gillnet loss from the WASS commercial salmon fishery through interviews with fishers and industry professionals and analysis of historical fishing effort. Major causes of gillnet loss included lack of experience, operator error, equipment malfunction, overcrowding of fishing grounds, mismatch of net depth with ocean depth, and more. The findings suggest that gillnet loss is currently much less frequent than in previous decades characterized by heavy fishing effort (i.e., 1970s – 1980s). Analysis of net removal records identified patterns of association between net fishing depths and depths at which derelict nets are found. Spatial analysis and ArcGIS were used to produce a simple model capable of identifying areas of high, moderate and low probability of derelict gillnet occurrence. This model was applied to the British Columbia waters of the Salish Sea (BCSS) where an organized derelict fishing gear removal operation has been identified as a need, but has not yet been implemented. This study refines previous estimates of derelict gillnet quantities in the WASS, identifies the major causes for derelict gillnet loss and produces an exportable model that can be used to assist the design and implementation of derelict fishing gear surveys and removal efforts in British Columbia and beyond. Plans are underway to conduct derelict net surveys and removals in specific locations of the BCSS in 2014, and in turn, test the accuracy of the model reported here.

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May 2nd, 1:30 PM May 2nd, 3:00 PM

Derelict Gillnets in the Salish Sea: Causes of Gillnet Loss, Extent of Accumulation and Development of a Predictive Transboundary Model

Room 613-614

From 2002 through the end of 2012, a total of 4,358 derelict nets were removed from the Washington waters of the Salish Sea (WASS), 95% of which were gillnets. Forty-five percent of these gillnets were removed from low to high relief rocky substrate. I investigated the causes and rates of gillnet loss from the WASS commercial salmon fishery through interviews with fishers and industry professionals and analysis of historical fishing effort. Major causes of gillnet loss included lack of experience, operator error, equipment malfunction, overcrowding of fishing grounds, mismatch of net depth with ocean depth, and more. The findings suggest that gillnet loss is currently much less frequent than in previous decades characterized by heavy fishing effort (i.e., 1970s – 1980s). Analysis of net removal records identified patterns of association between net fishing depths and depths at which derelict nets are found. Spatial analysis and ArcGIS were used to produce a simple model capable of identifying areas of high, moderate and low probability of derelict gillnet occurrence. This model was applied to the British Columbia waters of the Salish Sea (BCSS) where an organized derelict fishing gear removal operation has been identified as a need, but has not yet been implemented. This study refines previous estimates of derelict gillnet quantities in the WASS, identifies the major causes for derelict gillnet loss and produces an exportable model that can be used to assist the design and implementation of derelict fishing gear surveys and removal efforts in British Columbia and beyond. Plans are underway to conduct derelict net surveys and removals in specific locations of the BCSS in 2014, and in turn, test the accuracy of the model reported here.