Abstract
Bycatch in commercial fisheries is a pressing conservation concern and has spurred global interest in adopting ecosystem-based management practices. To address such concerns, a thorough understanding of spatiotemporal relationships among bycatch species, their environment and fisheries is required. Here we used a generalized linear mixed model framework incorporating spatiotemporal random effects to model abundance patterns for 3 skate species caught as bycatch in commercial fisheries (thorny skate Amblyraja radiata, winter skate Leucoraja ocellata and smooth skate Malacoraja senta), as well as 10 target species on the Scotian Shelf, NW Atlantic. Spatiotemporal estimates of relative abundance for at-risk skates within the years 2005-2015 were modelled from research trawl survey data and overlaid with those for target species to identify hotspots of bycatch risk. In addition, abundance estimates for at-risk skates within the years 1975-1985, a period of higher stock abundance, were used to identify areas of previously important habitat. Historically, skate species densely occupied areas near Sable Island and Banquereau Banks, Georges Bank and the Bay of Fundy. Bycatch hotspots between at-risk skates and commercial targets were identified in regions across the Scotian Shelf. These hotspots were independently validated by predicting species presence from at-sea observer data that monitor skate bycatch directly. We discuss spatial relationships between target and bycatch species, highlighting limitations of at-sea observer programmes that this method helps to address. This framework can be applied more broadly to inform ecosystem management and priority areas for conservation or fisheries regulation.
Highlights
Sustained exploitation of fisheries worldwide has left nearly half of scientifically assessed fish stocks currently in an overfished state (Hilborn et al 2020) and has reduced many populations of incidentally caught species to low abundance (Lewison et al 2004, 2014, Beddington et al 2007, Sims & Queiroz 2016, Pacoureau et al 2021)
Our study aimed to present a modelling framework to identify spatial areas of conservation priority for depleted species affected as bycatch by multiple fisheries
We used a longstanding scientific research vessel (RV) survey dataset and Generalized linear mixed models (GLMMs) to evaluate the distribution of skates prior to heavy exploitation in order to map important habitat areas for each species
Summary
Sustained exploitation of fisheries worldwide has left nearly half of scientifically assessed fish stocks currently in an overfished state (Hilborn et al 2020) and has reduced many populations of incidentally caught species to low abundance (Lewison et al 2004, 2014, Beddington et al 2007, Sims & Queiroz 2016, Pacoureau et al 2021) In response to these multi-species challenges, fisheries management authorities have aimed to move towards ecosystembased approaches to ocean resource management. Traditional methods to mitigate deleterious effects of fishing and protect habitat involve static area closures, establishment of marine protected areas and modifications to fishing gear and practices (Cox et al 2007, Poisson et al 2014, Senko et al 2014) These often result in trade-offs between protecting a species or habitat, and maintaining economically viable fisheries (O’Keefe et al 2014). A more dynamic ecosystem-based management approach, where regulations shift in space and time in a fluid response to changes in biological and oceanographic parameters, is widely viewed as a possible solution (O’Keefe & DeCelles 2013, Maxwell et al 2015, Hazen et al 2018, Welch et al 2020)
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