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

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 datashari...

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Main Authors: 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
Format: Other/Unknown Material
Language:unknown
Published: 2021
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Online Access:https://zenodo.org/record/4658502
https://doi.org/10.5281/zenodo.4658502
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spelling ftzenodo:oai:zenodo.org:4658502 2023-05-15T17:36:22+02:00 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 2021-04-01 https://zenodo.org/record/4658502 https://doi.org/10.5281/zenodo.4658502 unknown info:eu-repo/grantAgreement/EC/H2020/678760/ doi:10.5281/zenodo.4658501 https://zenodo.org/communities/atlas https://zenodo.org/record/4658502 https://doi.org/10.5281/zenodo.4658502 oai:zenodo.org:4658502 info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode info:eu-repo/semantics/other other 2021 ftzenodo https://doi.org/10.5281/zenodo.465850210.5281/zenodo.4658501 2023-03-11T04:27:58Z 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 ... Other/Unknown Material North Atlantic Zenodo
institution Open Polar
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op_collection_id ftzenodo
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description 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 ...
format Other/Unknown Material
author 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
spellingShingle 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
ATLAS Deliverable 3.3: Biodiversity, biogeography and GOODS classification system under current climate conditions and future IPCC scenarios
author_facet 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
author_sort Morato, T
title ATLAS Deliverable 3.3: Biodiversity, biogeography and GOODS classification system under current climate conditions and future IPCC scenarios
title_short ATLAS Deliverable 3.3: Biodiversity, biogeography and GOODS classification system under current climate conditions and future IPCC scenarios
title_full ATLAS Deliverable 3.3: Biodiversity, biogeography and GOODS classification system under current climate conditions and future IPCC scenarios
title_fullStr ATLAS Deliverable 3.3: Biodiversity, biogeography and GOODS classification system under current climate conditions and future IPCC scenarios
title_full_unstemmed ATLAS Deliverable 3.3: Biodiversity, biogeography and GOODS classification system under current climate conditions and future IPCC scenarios
title_sort atlas deliverable 3.3: biodiversity, biogeography and goods classification system under current climate conditions and future ipcc scenarios
publishDate 2021
url https://zenodo.org/record/4658502
https://doi.org/10.5281/zenodo.4658502
genre North Atlantic
genre_facet North Atlantic
op_relation info:eu-repo/grantAgreement/EC/H2020/678760/
doi:10.5281/zenodo.4658501
https://zenodo.org/communities/atlas
https://zenodo.org/record/4658502
https://doi.org/10.5281/zenodo.4658502
oai:zenodo.org:4658502
op_rights info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/4.0/legalcode
op_doi https://doi.org/10.5281/zenodo.465850210.5281/zenodo.4658501
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