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ATLAS Deliverable 3.3: Biodiversity, biogeography and GOODS classification system under current climate conditions and future IPCC scenarios

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


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  <titles>
    <title>ATLAS Deliverable 3.3: Biodiversity, biogeography and GOODS classification system under current climate conditions and future IPCC scenarios</title>
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  <publisher>Zenodo</publisher>
  <publicationYear>2021</publicationYear>
  <dates>
    <date dateType="Issued">2021-04-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Other"/>
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    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4658501</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/atlas</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Major knowledge gaps and a lack of refined models and cost-effective tools to monitor and predict&lt;br&gt;
biodiversity delay agreement and implementation of biodiversity management policies at the highest&lt;br&gt;
levels. These delays will be reduced through cross-sectoral, multi-stakeholder trans-Atlantic datasharing&lt;br&gt;
and integration of ocean mixing and food supply into biodiversity maps. The main vision of&lt;br&gt;
WP3 Biodiversity and Biogeography is to conduct pilot studies to validate robust and cost-effective&lt;br&gt;
techniques to minimise uncertainty in deep ocean biodiversity and biogeography assessment.&lt;br&gt;
At international levels, the Global Open Oceans and Deep Seabed (GOODS) classification scheme is a&lt;br&gt;
decision-support tool to help safeguard marine biodiversity, support the ecosystem approach, marine&lt;br&gt;
spatial management and the design of MPA networks in national waters and in the international High&lt;br&gt;
Seas, thereby helping nations implement global policies enshrined by UNCLOS (e.g. ABNJs), the FAO&lt;br&gt;
(e.g. VMEs) and the CBD (e.g. EBSAs). GOODS integrates layers of physical and biological information&lt;br&gt;
to delineate biogeographic provinces as entities of flora, fauna and environmental settings. It was later&lt;br&gt;
adapted for ABNJ waters &amp;gt;800 m deep, delineating a &amp;ldquo;Northern Atlantic boreal&amp;rdquo; and a &amp;ldquo;North Atlantic&amp;rdquo;&lt;br&gt;
province based on distinct patterns of particulate organic carbon flux and water temperatures.&lt;br&gt;
However, the adapted scheme now needs further refinement in light of policy drivers such as the&lt;br&gt;
VMEs and EBSAs as it lacks input from structurally complex seabed environments such as CWC reefs,&lt;br&gt;
sponge grounds and hydrothermal vents that may also meet EBSA and VME criteria. It could also be&lt;br&gt;
substantially improved with input from the latest ocean models integrating horizontal and vertical&lt;br&gt;
mixing as water mass characteristics are critical for GOODS boundaries and for species distribution&lt;br&gt;
models (SDMs) to predict occurrences of cold-water corals, sponges and fish. Yet even SDMs that&lt;br&gt;
integrate larval tracking are still overly simplistic and inaccurate, and at best they use coarse estimates&lt;br&gt;
of surface primary production to proxy seafloor food supply.&lt;br&gt;
In this deliverable, ATLAS used a combination of techniques, along with the best available information&lt;br&gt;
along with knowledge developments made by WP1 and WP2 and new data gathered by WP3 to&lt;br&gt;
improve the understanding of deep-sea the biodiversity and biogeographic patterns of sensitive deepwater&lt;br&gt;
ecosystems and deep-sea fish in the North Atlantic and forecast changes under IPCC 21st century&lt;br&gt;
scenarios of water mass structure and ocean currents.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/678760/">678760</awardNumber>
      <awardTitle>A Trans-AtLantic Assessment and deep-water ecosystem-based Spatial management plan for Europe</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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