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Morato, T; González-Irusta, JM; Dominguez-Carrió, C; Wei, C-L; Davies, A; Sweetman, AK; Taranto, GH; Beazley, L; García-Alegre, A; Grehan, A; Laffargue, P; Murillo, FJ; Sacau, M; Vaz, S; Kenchington, E; Arnaud-Haond, S; Callery, O; Chimienti, G; Cordes, E; Egilsdottir, H; Freiwald, A; Gasbarro, R; Gianni, M; Gilkinson, K; Wareham Hayes, VE; Hebbeln, D; Hedges, K; Henry, L-A; Kazanidis, G; Koen-Alonso, M; Lirette, C; Mastrototaro, F; Menot, L; Molodtsova, T; Durán Muñoz, P; Murton, B; Orejas, C; Pennino, MG; Puerta, P; Ragnarsson, SA; Ramiro-Sánchez, B; Rice, J; Rivera, J; Roberts, JM; Rodrigues, L; Ross, SW; Rueda, JL; Snelgrove, P; Stirling, D; Treble, M; Urra, J; Vad, J; Watling, L; Walkusz, W; Wang, Z; Wienberg, C; Woillez, M; Levin, LA; Neat, F; Das, D; Fauconnet, L; Viegas, C; Afonso, P; Menezes, G; Pinho, MR; Silva, H; Rosa, A; Catarino, D; Giacomello, E; Guijarro, J; Cleland , J; Yeo, I; Xavier, JR; Sampaio, I; Spearman, J; Victorero, L; Messing, CG; Bilan, M; Blasco-Ferre, J; Bourillet, J-F; de Chambure, L; Davies, JS; Frank, N; Guillaumont, B; Georgoulas, K; Berx, B; Olu, K; Ramos, M; Ramalho, L; Renones, O; Caballero, JA; Tempera, F; Tourolle, J; Utrilla, O; van den Beld, I; Yashayaev, I; Serrano, A; Grasshoff, M; Rochette, S; Pham, CK; Carreiro-Silva, M
Major knowledge gaps and a lack of refined models and cost-effective tools to monitor and predict
biodiversity delay agreement and implementation of biodiversity management policies at the highest
levels. These delays will be reduced through cross-sectoral, multi-stakeholder trans-Atlantic datasharing
and integration of ocean mixing and food supply into biodiversity maps. The main vision of
WP3 Biodiversity and Biogeography is to conduct pilot studies to validate robust and cost-effective
techniques to minimise uncertainty in deep ocean biodiversity and biogeography assessment.
At international levels, the Global Open Oceans and Deep Seabed (GOODS) classification scheme is a
decision-support tool to help safeguard marine biodiversity, support the ecosystem approach, marine
spatial management and the design of MPA networks in national waters and in the international High
Seas, thereby helping nations implement global policies enshrined by UNCLOS (e.g. ABNJs), the FAO
(e.g. VMEs) and the CBD (e.g. EBSAs). GOODS integrates layers of physical and biological information
to delineate biogeographic provinces as entities of flora, fauna and environmental settings. It was later
adapted for ABNJ waters >800 m deep, delineating a “Northern Atlantic boreal” and a “North Atlantic”
province based on distinct patterns of particulate organic carbon flux and water temperatures.
However, the adapted scheme now needs further refinement in light of policy drivers such as the
VMEs and EBSAs as it lacks input from structurally complex seabed environments such as CWC reefs,
sponge grounds and hydrothermal vents that may also meet EBSA and VME criteria. It could also be
substantially improved with input from the latest ocean models integrating horizontal and vertical
mixing as water mass characteristics are critical for GOODS boundaries and for species distribution
models (SDMs) to predict occurrences of cold-water corals, sponges and fish. Yet even SDMs that
integrate larval tracking are still overly simplistic and inaccurate, and at best they use coarse estimates
of surface primary production to proxy seafloor food supply.
In this deliverable, ATLAS used a combination of techniques, along with the best available information
along with knowledge developments made by WP1 and WP2 and new data gathered by WP3 to
improve the understanding of deep-sea the biodiversity and biogeographic patterns of sensitive deepwater
ecosystems and deep-sea fish in the North Atlantic and forecast changes under IPCC 21st century
scenarios of water mass structure and ocean currents.