Drivers of spatiotemporal variability in bycatch of a top marine predator: First evidence for the role of water turbidity in protected species bycatch

• Main Authors: Luck, Cian, Cronin, Michelle, Gosch, Martha, Healy, Kieran, Cosgrove, Ronan, Tully, Oliver, Rogan, Emer, Jessopp, Mark
• Format: Dataset
• Language: unknown
• Published: 2019
• Subjects: bycatch; grey seal; Harbour seal; gillnet; Turbidity; Earth observation; harbour seal
• Online Access: https://zenodo.org/record/4989312; https://doi.org/10.5061/dryad.z34tmpg8c

1. Bycatch of protected species in static net fisheries is a global conservation concern and is currently considered the dominant anthropogenic threat to many marine mammal species worldwide. Effective bycatch mitigation remains challenging, contingent on an understanding of the underlying mechanisms that cause individuals to become entangled. 2. We combined data collected by scientific observers and fishers to identify predictors of seal bycatch in static net fisheries along the west, southwest, and south coasts of Ireland. We first analysed the broad regional and seasonal trends in seal bycatch before identifying environmental variables that could potentially explain these patterns. 3. Based on negative binomial generalised linear mixed effects models, the rate of seal bycatch significantly varied with season and region, and decreased at greater distances to major seal colonies and lower water turbidity. 4. Synthesis and applications. Our results suggest that distance to major seal colonies was a significant driver of the observed regional differences in seal bycatch rates, and water turbidity a major driver of seasonal trends. These findings will enable us to identify future bycatch risk and target mitigation measures accordingly. This is the first study to identify the effect of water turbidity on bycatch of a protected marine species. Increasing net visibility in turbid waters may provide a novel approach to mitigating against protected species bycatch in static net fisheries.05-Nov-2019 Field descriptors: vessel_id - unique identifier for each fishing vessel net_type - one of four entangling net types (see paper for more detailed description): gill - gillnets tangle - tangle nets trammel - trammel nets spider - spider nets (large mesh tangle nets) year - year data was recorded effort_km - net length in km soak_days - number of days the net has been left to soak in the water unattended effort_soak_km - fishing effort as the product of effort_km and soak_days depth - depth of the seafloor where the nets ...