ATLAS Deliverable 3.3: Biodiversity, biogeography and GOODS classification system under current climate conditions and future IPCC scenarios
Creators: name: Morato, T
name: González-Irusta, JM
name: Dominguez-Carrió, C
name: Wei, C-L
name: Davies, A
name: Sweetman, AK
name: Taranto, GH
name: Beazley, L
name: García-Alegre, A
name: Grehan, A
name: Laffargue, P
name: Murillo, FJ
name: Sacau, M
name: Vaz, S
name: Kenchington, E
name: Arnaud-Haond, S
name: Callery, O
name: Chimienti, G
name: Cordes, E
name: Egilsdottir, H
name: Freiwald, A
name: Gasbarro, R
name: Gianni, M
name: Gilkinson, K
name: Wareham Hayes, VE
name: Hebbeln, D
name: Hedges, K
name: Henry, L-A
name: Kazanidis, G
name: Koen-Alonso, M
name: Lirette, C
name: Mastrototaro, F
name: Menot, L
name: Molodtsova, T
name: Durán Muñoz, P
name: Murton, B
name: Orejas, C
name: Pennino, MG
name: Puerta, P
name: Ragnarsson, SA
name: Ramiro-Sánchez, B
name: Rice, J
name: Rivera, J
name: Roberts, JM
name: Rodrigues, L
name: Ross, SW
name: Rueda, JL
name: Snelgrove, P
name: Stirling, D
name: Treble, M
name: Urra, J
name: Vad, J
name: Watling, L
name: Walkusz, W
name: Wang, Z
name: Wienberg, C
name: Woillez, M
name: Levin, LA
name: Neat, F
name: Das, D
name: Fauconnet, L
name: Viegas, C
name: Afonso, P
name: Menezes, G
name: Pinho, MR
name: Silva, H
name: Rosa, A
name: Catarino, D
name: Giacomello, E
name: Guijarro, J
name: Cleland, J
name: Yeo, I
name: Xavier, JR
name: Sampaio, I
name: Spearman, J
name: Victorero, L
name: Messing, CG
name: Bilan, M
name: Blasco-Ferre, J
name: Bourillet, J-F
name: de Chambure, L
name: Davies, JS
name: Frank, N
name: Guillaumont, B
name: Georgoulas, K
name: Berx, B
name: Olu, K
name: Ramos, M
name: Ramalho, L
name: Renones, O
name: Caballero, JA
name: Tempera, F
name: Tourolle, J
name: Utrilla, O
name: van den Beld, I
name: Yashayaev, I
name: Serrano, A
name: Grasshoff, M
name: Rochette, S
name: Pham, CK
name: Carreiro-Silva, M
Publisher: name: Zenodo
Year: 2021

description: Major knowledge gaps and a lack of refined models and cost-effective tools to monitor and predict<br> biodiversity delay agreement and implementation of biodiversity management policies at the highest<br> levels. These delays will be reduced through cross-sectoral, multi-stakeholder trans-Atlantic datasharing<br> and integration of ocean mixing and food supply into biodiversity maps. The main vision of<br> WP3 Biodiversity and Biogeography is to conduct pilot studies to validate robust and cost-effective<br> techniques to minimise uncertainty in deep ocean biodiversity and biogeography assessment.<br> At international levels, the Global Open Oceans and Deep Seabed (GOODS) classification scheme is a<br> decision-support tool to help safeguard marine biodiversity, support the ecosystem approach, marine<br> spatial management and the design of MPA networks in national waters and in the international High<br> Seas, thereby helping nations implement global policies enshrined by UNCLOS (e.g. ABNJs), the FAO<br> (e.g. VMEs) and the CBD (e.g. EBSAs). GOODS integrates layers of physical and biological information<br> to delineate biogeographic provinces as entities of flora, fauna and environmental settings. It was later<br> adapted for ABNJ waters &gt;800 m deep, delineating a “Northern Atlantic boreal” and a “North Atlantic”<br> province based on distinct patterns of particulate organic carbon flux and water temperatures.<br> However, the adapted scheme now needs further refinement in light of policy drivers such as the<br> VMEs and EBSAs as it lacks input from structurally complex seabed environments such as CWC reefs,<br> sponge grounds and hydrothermal vents that may also meet EBSA and VME criteria. It could also be<br> substantially improved with input from the latest ocean models integrating horizontal and vertical<br> mixing as water mass characteristics are critical for GOODS boundaries and for species distribution<br> models (SDMs) to predict occurrences of cold-water corals, sponges and fish. Yet even SDMs that<br> integrate larval tracking are still overly simplistic and inaccurate, and at best they use coarse estimates<br> of surface primary production to proxy seafloor food supply.<br> In this deliverable, ATLAS used a combination of techniques, along with the best available information<br> along with knowledge developments made by WP1 and WP2 and new data gathered by WP3 to<br> improve the understanding of deep-sea the biodiversity and biogeographic patterns of sensitive deepwater<br> ecosystems and deep-sea fish in the North Atlantic and forecast changes under IPCC 21st century<br> scenarios of water mass structure and ocean currents.