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Distribution models of deep-sea elasmobranchs in the Azores, Mid-Atlantic Ridge, to inform spatial planning
Das, D.; González-Irusta, J.M.; Morato, T.; Fauconnet, L.; Catarino, D.; Afonso, P.; Viegas, C.; Rodrigues, L.; Menezes, G.; Rosa, A.; Pinho, M.R.R.; Marques da Silva, H.; Giacomello, E. (2022). Distribution models of deep-sea elasmobranchs in the Azores, Mid-Atlantic Ridge, to inform spatial planning. Deep-Sea Res., Part 1, Oceanogr. Res. Pap. 182: 103707. https://dx.doi.org/10.1016/j.dsr.2022.103707
In: Deep-Sea Research, Part I. Oceanographic Research Papers. Elsevier: Oxford. ISSN 0967-0637; e-ISSN 1879-0119, meer
Peer reviewed article  
Beschikbaar in  Auteurs | Dataset 
Trefwoord
    Marien/Kust
Author keywords
    Threatened species; Generalised additive models; Delta GAMs; Deep-sea fisheries; Fisheries management; Azores archipelago; North Atlantic Ocean
Project Top | Auteurs | Dataset 
  • Towards the Sustainable Development of the Atlantic Ocean: Mapping and Assessing the present and future status of Atlantic marine ecosystems under the influence of climate change and exploitation, meer
Auteurs  Top | Dataset 
  • Das, D.
  • González-Irusta, J.M.
  • Morato, T.
  • Fauconnet, L.
  • Catarino, D.
  • Afonso, P.
  • Viegas, C.
  • Rodrigues, L.
  • Menezes, G.
  • Rosa, A.
  • Pinho, M.R.R.
  • Marques da Silva, H.
  • Giacomello, E.
Abstract
    Elasmobranchs inhabiting depths beyond 200 m are extremely susceptible to overexploitation but are extracted by fisheries around the world either as target species or as bycatch. There is little information available to formulate management strategies to reduce elasmobranch-fishery interactions in the deep sea. In European Union waters, prohibiting the catches of deep-sea elasmobranchs has provided the necessary impetus to study by-catch avoidance of these threatened species. We used over 20 years of fisheries-independent and fisheries-dependent data to model the spatial distribution of 15 species of deep-sea elasmobranchs (12 sharks and 3 rays) captured frequently in the Exclusive Economic Zone of the Azores Archipelago (Mid-Atlantic Ridge) to explore spatial management to reduce unwanted catches of these species. We applied Generalised Additive Models to predict the probability of presence of 15 species, as well as the abundance of 6 of those species, within the Azores EEZ and neighbouring seamounts (up to 2000 m depth), using environmental and operational variables as predictors. Our results identified that depth is most influential in determining the distribution of these sharks and rays, in addition to seafloor topography. Distinctive bathymetric features such as seamounts and ridges were highlighted as areas where the probability of presence of the greatest number of species overlapped. Although not related to habitat, gear type influenced the capture probability of certain species, with the artisanal handline, gorazeira, having lower captures than bottom longline. Our results support using depth-based, area-based, and gear-based tactics to design management measures to reduce elasmobranch bycatch, for more sustainable deep-sea fisheries.
Dataset
  • González-Irusta, José Manuel; Fauconnet, Laurence; Das, Diya; Catarino, Diana; Afonso, Pedro; Viegas, Cláudia Neto; Rodrigues, Luís; Menezes, Gui M; Rosa, Alexandra; Pinho, Mário Rui Rilhó; Silva, Hélder Marques da; Giacomello, Eva; Morato, Telmo (2022): Outputs of predictive distribution models of deep-sea elasmobranchs in the Azores EEZ (down to 2,000m depth) using Generalized Additive Models. PANGAEA., meer
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